In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
\r\n", "abstract": "In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "antes_sebastian-2026-msc", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "telaar_sina-2026-baa", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" } ], "keywords": [], "weblinks": [ { "href": "https://dl.ccf.org.cn/institude/institudeDetail?id=4320599515842560&_ack=1", "caption": null, "description": null, "main_file": 0 } ], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "wu-2019-report-paper.pdf", "type": "application/pdf", "size": 8399742, "path": "Publication:wu-2019-report", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/wu-2019-report-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/wu-2019-report-paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "BioNetIllustration", "workgroup_id": "vis", "drupal_id": 4196, "drupal_path": "/research/projects/BioNetIllustration", "name": "BioNetIllustration: User Centric Illustrations of Biological Networks", "name_de": null, "short_title": "BioNetIllustration", "website": null, "status": "active", "short_abstract": "In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
\r\n", "abstract": "In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public. Acknowledgment: The project has received funding from the European Union Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 747985.
\r\n", "start_date": "2017-06-21", "end_date": "2019-06-20", "leader_id": 1464, "logo": { "name": "logo.png", "path": "project:BioNetIllustration", "type": "image/png", "size": 16337, "orig_name": "logo.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "Horizon 2020", "contract_number": "747985", "comment": null } ], "research_areas": [ "BioVis", "InfoVis" ], "publications": [ "cmolik-2020-tvcg", "kouril-2018-LoL", "mizuno-2019-eurovis", "Purchase-2020-gd", "rinortner_susanne-2019-vpicc", "Sbardellati-2019-vcbm", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "YOGHOURDJIAN2019" ], "url": "https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration", "__class": "Project" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2019/wu-2019-report/", "__class": "Publication" }, { "id": "Miao_2019", "type_id": "journalpaper_notalk", "tu_id": 272339, "repositum_id": null, "title": "Multiscale Molecular Visualization", "date": "2019-01", "abstract": "We provide a high-level survey of multiscale molecular visualization techniques, with a focus on application-domain questions, challenges, and tasks. We provide a general introduction to molecular visualization basicsand describe a number of domain-specific tasks that drive this work. These tasks, in turn, serve as the generalstructure of the following survey. First, we discuss methods that support the visual analysis of moleculardynamics simulations. We discuss, in particular, visual abstraction and temporal aggregation. In the secondpart, we survey multiscale approaches that support the design, analysis, and manipulation of DNAnanostructures and related concepts for abstraction, scale transition, scale-dependent modeling, andnavigation of the resulting abstraction spaces. In the third part of the survey, we showcase approaches thatsupport interactive exploration within large structural biology assemblies up to the size of bacterial cells.We describe fundamental rendering techniques as well as approaches for element instantiation, visibilitymanagement, visual guidance, camera control, and support of depth perception. We close the survey with abrief listing of important tools that implement many of the discussed approaches and a conclusion thatprovides some research challenges in the field.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 323, "image_height": 240, "name": "Miao_2019-image.JPG", "type": "image/jpeg", "size": 32385, "path": "Publication:Miao_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/Miao_2019-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/Miao_2019-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "gall_alexander_2016BA", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Miao_2015_VCBM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2018", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao2018Dimsum", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": 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Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" } ], "keywords": [ "molecular visualization", "molecular dynamics", "modelitics", "DNA nanotechnology", "visual abstraction" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 323, "image_height": 240, "name": "Miao_2019-image.JPG", "type": "image/jpeg", "size": 32385, "path": "Publication:Miao_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/Miao_2019-image.JPG", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/Miao_2019-image:thumb{{size}}.png" }, { "description": null, "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Miao_2019-Paper.pdf", "type": "application/pdf", "size": 6728324, "path": "Publication:Miao_2019", "url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/Miao_2019-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2019/Miao_2019/Miao_2019-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ { "id": "vis", "drupal_id": 1354, "name": "Visualization Group", "website": "https://www.cg.tuwien.ac.at/group/Visualization-Group", "projects": [ "ADAPT", "AngioVis", "Animated Cell Tab development", "AutARG", "avr", "BioNetIllustration", "COMRADE", "d10027", "d10162", "d10164", "d10206", "d10214", "d10413", "d10450", "d10489", "d4328", "d4335", "d4534", "d9275", "d9282", "d9522", "d9555", "d9671", "d9951", "deskollage", "diagvis", "exvisation", "Illustrare", "illvisation", "KASI", "ManyViews", "NeuroViewer", "ProcessIllVis", "ProKeyAnim", "PVG", "Scale-VS", "Scenario Pool", "Semantic Steering", "Sim-CT", "Smart-CT", "Smile Analytics", "ViMaL", "VISAR" ], "research_areas": [ "BioVis", "IllVis", "InfoVis", "MedVis", "NetVis", "Perception", "VisMat", "VR" ], "publications": [ "2013_Viola_Ivan_2013_MTS", "2015-image-coll", "2017-kouril-illcell", "2019-ic", "AA2020", "aigner-2025-vhv", "alacruzECR2004", "alacruzVisSym2004", "Alharbi_2021", "Alsallakh_2012_RCW", "alsallakh-2009-iva", "altendorfer-2008-vts", "amabili2021", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "amirkhanov2010AMA", "ammer-2008-lst", "An-2018-CHI", "AndreUrsits_2013_APP", "antes-2023-vhv", "Antonini2020", "arbesser_ba_2023", "Artner-2004-Hig", "Artner-2005-Hig", "Artner-2005-Thesis", "audioflow", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Balabanian-2010-PSDSV", "Balduz_01", "Basch_2011_ATA", "Bauer_David_2018", "Bauer_Johannes_2014_IWB", "bauer-2015-cbfd", "Bayat_2019", "bayer-2015-gapaot", "bbeer-2013", "Bechtold2020", "Beer_2011_DVE", "Beham_Michael_PSC", "beham-2014-cupid", "bernhard-2006-dvrcta", "bernhard-2014-GTOM", "bernhard-2016-gft", "Bernold_2019", "bernold-2019-epr", "bhore-2021-issac", "birkeland_aasmund_2014_pums", "Birkeland-2012-IMC", "BirsakHanzl-2009", "boeroendy-2022-uio", "boesch_2014_browserHistoryVis", "borgo-2013-gly", "borondy2022", "bouzari-thesis", "bramberger-3pv", "Brandorff-08-OV", "brandorff-2009-erv", "brandstaetter_01", "brandstaetter-2007-vosd", "Brandstaetter2020", "Braunsperger-2025_bsc", "breitenecker-2020-bct", "bront-2023-svo", "brucker-2010-RES", "Bruckner_Stefan_2015_VAS", "bruckner-2004-EVV", "bruckner-2005-AIV", "bruckner-2005-ATI", "bruckner-2005-ICV", "bruckner-2005-vid", "bruckner-2005-VIS", "bruckner-2006-EVV", "bruckner-2006-ICE", "bruckner-2007-EDF", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2008-IVV", "bruckner-2009-BVQ", "bruckner-2009-IVV", "bruckner-2010-HVC", "bruckner-2010-IFC", "bruckner-2010-ISM", "bruckner-2010-SES", "Bruckner-2012-VEA", "buerger_raphael_2006_3dpoly", "Buerger-2007-cmv", "Buerger-2007-eurovis", "buerger-2007-star", "bugnar-esk-2021", "burns-2007-fea", "bydlinski-2015-gapaot", "byska-2019-mdfc", "Cai_2018", "Caic2021", "Carata_2011_IVE", "carbesser-2013", "casellato-2016-pkg", "cellVIEW_2015", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "Cornel_Daniel_2015_VOC", "Cornel2016CFM", "coto-2005-MAC", "Cruz-thesis", "Csebfalvi-2002-FPVF", "Csebfalvi-2002-SBICG", "Csebfalvi-2002-Smo", "Csebfalvi-2012-IOM", "Csuk_2011", "daae-lampe-2010-dif", "dataset-christmastree", "dataset-present", "dataset-stagbeetle", "Deutsch-2018", "Dhanoa_2021", "dhanoa-2025-ave", "Dhanoa2024", "Diehl_2015", "Diehl_2021", "Diehl-2017-Albero", "Dietrich_1", "dietrich-2016-viseq2", "diss-thesis-bratislava", "diss-thesis-magdeburg", "diss-thesis-siegen", "djuric-2020-wvo", "donabauer_2019_1", "donabauer-2015-asc", "draeger-2005-chain", "dworschak-2016-szcm", "dworschak-2016-szcm", "dworschak-2024-aml", "Eckelt_2017", "Eckelt_2018_01", "Edi_2019_10_01", "edlinger-2018-vwr", "eg-tut2005-iv", "Ehlers_PhD", "ehlers-2023-iro", "ehlers-2024-mmm", "ehlers-2024-vgs", "ehlers-2025-ait", "Eichner2022", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "emsenhuber-2008-vhd", "erler-2025-lidarscout", "eschner-2023-evl", "eschner-2023-ims", "eschner-2025-ide", "eschner-blur-2022", "Escribano_2017", "Essler2022", "EuroVis2018-ShortPapers-Karall", "EuroVis2018-ShortPapers-Reiter", "facial2004", "Fechter_2011_DBS", "filipovic-2014-dect", "FISCHL-2012-CTASEG", "fmistelbauer-2014-ad", "fmistelbauer-2014-adict", "Ford-2012-HRV", "fourousan2021", "freiler-2008-ste", "fritz-2009-ieq", "Froehler_Berhnard_2015_ESM", "froschauer-2009-iod", "Fruehstueck_Anna_2015_DOM", "fuchs_raphael_2007_par", "fuchs_vhml", "fuchs-2008-del", "fuchs-vortex", "furmanova_2020", "gadllah_2016", "Gadllah_Hani_2016", "gall_2016", "Gall_2017", "gall_alexander_2016BA", "gall-2025-marv", "Gall2020", "Gall2021", "gangl-2018-gpsart", "Ganglberger-2022-cg", "ganglberger2019", "Ganuza", "Ganuza_2015", "Ganuza_MJ_2015_AVe", "Ganuza_ML_2015_ISA", "Ganuza-2017-IVCSGM", "Gavrilescu_2011_VGP", "gavrilescu-2008-vsc", "gavrilescu-2009-postrend", "Gavrilescu-2010-CIE", "Gehrer_Daniel_CUI", "Gehrer-2017", "Gehrer-2017-molmach", "georgiev-2019-cbg", "gerl-2006-vhi", "geymayer-2017-std", "Gietl_2020", "Gillmann2021", "glanznig-2009-LAMC", "glinzner-2016-tex", "goel-2024-rdr", "Gogel2020", "gostler-2015-3dp", "grammatikaki-2025-htr", "grammatikaki-thesis", "grimm-2004-arefined", "GRIMM-2004-FDMX-P", "grimm-2004-memory", "GRIMM-2004-PPC", "grimm-2004-volume", "Groeller_2011_CVC", "Groeller_2011_CW", "Groeller_2011_GBC", "Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", 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"wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2018/miao_plitvice_2018/", "__class": "Publication" }, { "id": "Miao2018FDN", "type_id": "poster", "tu_id": null, "repositum_id": null, "title": "A Preview to Adenita: Visualization and Modeling of DNA Nanostructures", "date": "2018-06-08", "abstract": "We present Adenita, an open-source software that aims to provide an integrated in silico\ndesign toolkit for DNA Nanostructures. It facilitates the modular assembly of pre-existing\nand de novo designs, regardless of the used approach. Adenita is being developed in the\ncontext of the MARA project [1], a highly ambitious project aiming to produce a DNA\nnanorobot capable of targeted cell lyses. Currently, the existing design and visualization\ntools are insufficient to solve the specific challenges in our project. We aim to overcome\nthese limitations with Adenita, a new semi-automated approach that we are developing as\nthe MARA project advances. Adenita integrates visualizations [2] with user interactions and\nalgorithms in a semi-manual approach. At the core, we use a hierarchical data model that\nenables us to combine both a top-down (DAEDALUS [3]) and a bottom-up (caDNAno [4])\ndesign approach of the DNA Nanostructure. From the DNA data model, we create smooth\nvisualizations that depict the structure in multiple scales from its atomic details to a highlevel\ngeometric representation of the target shape. In addition, we employ different layouts\nfor the same structure [5]: 3D structural representations, 2D caDNAno-style diagrams, and\n1D display of the linear sequences. Creators enable the parametrized generation of\nstructural motifs, while Manipulators facilitate the advanced modifications of the structural\nproperties, such as connecting components and adding bridging strands. Analysis of the\ndesigns is still in a preliminary phase, but it already enables the straightforward estimation\nof distances and the melting temperatures [6] of binding regions. The first DNA\nnanostructures that we designed with the new tool are now under experimental evaluation.\n", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 857, "image_height": 1242, "name": "Miao2018FDN-image.png", "type": "image/png", "size": 1074408, "path": "Publication:Miao2018FDN", "url": "https://www.cg.tuwien.ac.at/research/publications/2018/Miao2018FDN/Miao2018FDN-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2018/Miao2018FDN/Miao2018FDN-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1474, "drupal_id": null, "orcid_id": null, "website": null, "firstname": "Elisa", "lastname": "De Llano", "searchname": "Elisa De Llano", "is_teacher": false, "name": "Elisa De Llano", "publications": [ "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN" ], "publications_first": [], "project_leader": [], "publication_field": [], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1474", "__class": "Author" }, { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], 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"publ_id": "Reisacher_Matthias_CPW", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sifuentes-2018-crowd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "sorger-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "textures-3d-printing", "field_id": "supervisor", "ordernum": 2 }, { "publ_id": "Thurner-2005-IVR", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "vad_2015_phd", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Viola_Ivan_2013_HQ3", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-05-Smart", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "viola-2007-ort", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "Viola-Pondering-2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "vis-foa", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "waldin-2017-thesis", "field_id": "supervisor", "ordernum": 0 }, { "publ_id": "Wihann_2017", "field_id": "supervisor", "ordernum": 0 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=171", "__class": "Author" } ], "date_from": "2017-06", "date_to": "2018-06", "event": "EuroVis Conference 2018", "journal": "Computer Graphics Forum", "lecturer": [ { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "gall_alexander_2016BA", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Miao_2015_VCBM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2018", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao2018Dimsum", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1263", "__class": "Author" } ], "location": "Brno, Czech Republic", "number": "3", "volume": "37", "research_areas": [ { "id": "BioVis", "drupal_id": 4127, "name": "Biological Data Visualization", "short_abstract": "In this research area, we develop new visualization techniques to support biologists in data analysis and create visualizations to disseminate scientific discoveries in biology.", "abstract": "In modern biological research domain experts have to deal with complex and large data collections and simulations. Our goal is to support biological researches in molecular biology and phenotyping communities by developing visualizations that complement statistical methodology and wet lab with visual data analysis. Our tools allow the domain experts to see the key information they are looking for that relates to the studied structure, such as tunnels in molecules on the nanoscale or root shape distributions on the macroscopic magnification levels.\nEqually important is the role of visualization in explaining certain phenomenon to a larger audience. Biologists create large structural models that reflect the state-of-the-art knowledge about a certain living organism. This form of captured knowledge can be effectively communicated with interactive visualization, especially the aspect of understanding interplay of multiple spatial and temporal scales. With our visualization technology audience can therefore seamlessly zoom from zoom level when seeing entire bacteria down to its atomic detail.\n", "website": "https://www.cg.tuwien.ac.at/research/area/BioVis", "teaser": { "name": "teaser.png", "path": "research_area:BioVis", "type": "image/png", "size": 16330957, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/BioVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "amirkhanov-2019-manylands", "byska-2019-mdfc", "cellVIEW_2015", "cmolik-2020-tvcg", "Dietrich_1", "dietrich-2016-viseq2", "Ehlers_PhD", "ehlers-2025-ait", "eschner-2023-ims", "eschner-blur-2022", "Escribano_2017", "Furmanova_2018", "Gehrer-2017", "Gehrer-2017-molmach", "glinzner-2016-tex", "Halladjian_2020", "kapferer-2017-godot", "klein_2017_IM", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "koch-2018-sso", "Kolesar-Fractional-2016", "kolesar-ivan-2014-polymers", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kozlikova-Visualization-2016b", "Krone2016VABC", "Kugler_2019", "lemuzic_2015_timelapse", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lipp-2017-mgpu", "lipp-2017-vulkan", "Manczarski-2016", "manylands_award", "Miao_2019", "miao_inria_2017", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-xmas-card-2016", "Mitterhofer_2017", "nguyen_2020-covid", "Nowak_2020", "raidou_2019_springer", "raidou_shonan167", "raidou2018visualflatter", "rasch-2016-imgses", "Reisacher2016", "rinortner_susanne-2019-vpicc", "Sarkis_2021", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2013-neuromap", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "stappen_2017_animatedcomic", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "trautner-2018-imd", "unger-2019_vcp", "vad_2015_phd", "vad_viktor-2017-WVE", "vad-2016-bre", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "waldin-2019-ccm", "waldner-2014-af", "Weissenboeck_2019", "wu-2017-dagstuhl", "wu-2018-metabo", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg" ], "projects": [ "BioNetIllustration", "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=BioVis", "__class": "ResearchArea" }, { "id": "IllVis", "drupal_id": 4131, "name": "Illustrative Visualization", "short_abstract": "In this research area, we develop rendering methods that are inspired by scientific illustrations, in order to make complex biological information more intuitive to understand and more pleasant to read.", "abstract": "Scientific illustration is concerned with researching ways in which complex biological and medical data can be abstracted in order to convey a desired information that would otherwise be impossible or hard to retrieve from the original data. Illustrators apply such techniques, for instance, to present non-important parts of an organ in a simplified way, while using detailed representations to put the focus of attention on a region where a tumor might be situated.\n\nTo identify such meaningful visual abstractions for visualization, their effectiveness for human perception and cognition has to be assessed, and they have to be formalized in order to make them applicable in rendering algorithms. In this project, we try to advance the understanding of procedural visual abstraction of complex physiological processes that describe the complex machinery of biological life.", "website": "https://www.cg.tuwien.ac.at/research/area/IllVis", "teaser": { "name": "teaser.jpg", "path": "research_area:IllVis", "type": "image/jpeg", "size": 34861, "orig_name": "teaser.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/IllVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "2017-kouril-illcell", "Alharbi_2021", "Antonini2020", "Balabanian-2010-IIV", "Balduz_01", "Bayat_2019", "Bechtold2020", "Birkeland-2012-IMC", "brandstaetter_01", "bruckner-2005-ICV", "bruckner-2006-ICE", "bruckner-2007-STF", "bruckner-2008-IIV", "bruckner-2010-HVC", "bruckner-2010-IFC", "cellVIEW_2015", "Chen-Information-2016", "Deutsch-2018", "Dhanoa_2021", "Dhanoa2024", "dietrich-2016-viseq2", "donabauer_2019_1", "eg-tut2005-iv", "eschner-2023-ims", "Essler2022", "gangl-2018-gpsart", "Gehrer_Daniel_CUI", "Gehrer-2017-molmach", "gerl-2006-vhi", "Gogel2020", "Groeller_2011_IPV", "Groeller_2016_I3", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_V1_2020", "groeller-2006-ivt", "groeller-2007-fci", "groeller-2008-irs", "Groeller-2010-IFI", "gruber-2025-vps", "Halladjian_2020", "haushofer-2018-skinning", "Heim_2020", "horvath-2018-ism", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Knapp_2017_CVR", "Koeppel2020", "kolesar-ivan-2014-polymers", "Konev-FCV2018", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "kroesl_x_card_2017", "Lackner_2022", "Langer_Edith_IR1", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "Leutschacher_2022", "ludwig-2012-MT", "Manczarski-2016", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "Melo_2018_11", "Meusburger_2020", "Miao_2019", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_stateKeylabTalk_2017", "miao2018Dimsum", "Michl_2017_CSV", "mindek-2015-mc", "mindek-2016-utah-talk", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-xmas-card-2016", "Moellinger_Christian_IDE2", "Niedermayer_2018", "Ortner_PhD", "Ortner2020", "pahr-2021-vologram", "Panayotov", "patel_daniel_2007_IRSD", "Pauschenwein_2022", "Peter_2012_AIV", "plank-2017-sldg", "prost-2016-molecule", "purgathofer-2008-cgi", "Radwan-2017-Occ", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-VF", "Reichinger_2016", "Reichinger_Fuhrmann_2016", "Reisacher_Matthias_CPW", "Reisacher2016", "Riegelnegg_2019", "rippl-2023-atg", "sbardellati_ba_2018", "Sbardellati-2019-vcbm", "schindler_2020vis", "schmidlehner2021", "scholz_2021", "Schrempf_2020", "schultes_lampi", "seyfert-2017", "sikachev-2010-ill_vis_vol_ren", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "Spechtenhauser_Florian_2016", "stappen_2017_animatedcomic", "Stoll2020", "sturl_2016_dynlabels", "Swoboda2020", "szabo_patrik-2022-tour", "takahashi-2019-acdt", "Thomas-2018", "TR-186-2-07-08", "Troidl_2021", "Troidl_2022", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "Unger2020", "Vasileva_2022", "Viola_Ivan_2013_SVA", "Viola_Ivan_CLD", "Viola_Ivan_IIP", "viola-evr", "Viola-Pondering-2017", "Viola-vistutillustrativevis", "Waldin_Nicholas_2016_Colormaps", "waldin-2019-ccm", "Waldner_2017_11", "Wihann_2017", "Woschizka_2021", "wu-2019-bmc", "wu-2019-report", "Zaufel_2021", "zechmeister2020", "Zeng_2021", "Zusag-2017-Bach" ], "projects": [ "Illustrare", "illvisation" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=IllVis", "__class": "ResearchArea" }, { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "antes_sebastian-2026-msc", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", 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"Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" }, { "id": "Illustrare", "workgroup_id": "vis", "drupal_id": 4189, "drupal_path": "/research/projects/Illustrare", "name": "ILLUSTRARE: Integrative Visual Abstraction of Molecular Data", "name_de": null, "short_title": "Illustrare", "website": null, "status": "active", "short_abstract": "FWF - I 2953-N31\nIntegrative Visual Abstraction of Molecular Data", "abstract": "In many aspects of our modern lives we face the problem of having to make sense of large amounts of data. This applies to scientists trying to make sense of their experiments and simulations, to bankers and traders trying to understand the dynamics of the financial markets, and to large enterprises which need to understand the principles behind demand and supply—to name just a few examples. The basic problem in all these cases is that people need to identify important and/or unexpected features in large simulated or captured datasets. Visualization is the domain that facilitates this process of sense-making by dramatically simplifying the process of obtaining an understanding of the data—by representing data visually and thus amplifying people’s cognition. This inherent capability of (good) visualization techniques to amplify human cognition, however, is no longer enough to be able to make sense of today’s huge datasets. To be able to see the essential aspects we need dedicated mechanisms that abstract away the (unnecessary) detail to, in turn, allow the user of the visualization to focus on the important elements. The crucial problem in this context is that it is impossible to know what is important and what is not in a general way—importance changes based on the research question, on the application domain, on the data size, on the user, on the specific situation, etc. Visualization technology therefore needs to support dynamic change of visual abstraction of the data to reflect these contextual changes. The fundamental research challenge in visualization for us is to get an understanding of what (visual) abstraction really is, what it means, how it can be controlled, and how it is, can be, and should be used in visualization.\n", "start_date": "2017-01-01", "end_date": "2019-12-31", "leader_id": 171, "logo": { "name": "logo.jpg", "path": "project:Illustrare", "type": "image/jpeg", "size": 95116, "orig_name": "logo.jpg", "thumb_url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare/logo:thumb{{size}}.png", "thumb_image_sizes": [ 120, 300 ] }, "funding_organisations": [ { "id": "fwf", "contract_number": "I 2953-N31", "comment": null } ], "research_areas": [ "BioVis", "IllVis" ], "publications": [ "Halladjian_2020", "kouril-2018-LoL", "lawonn-2018-illvisstar", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Viola-Pondering-2017" ], "url": "https://www.cg.tuwien.ac.at/research/projects/Illustrare", "__class": "Project" }, { "id": "illvisation", "workgroup_id": "vis", "drupal_id": 4171, "drupal_path": "/research/projects/illvisation", "name": "Visual Computing: Illustrative Visualization", "name_de": null, "short_title": "illvisation", "website": null, "status": "active", "short_abstract": "The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
The central focus of our research is to understand visual abstraction. Understanding means 1. to identify meaningful visual abstractions, 2. to assess their effectiveness for human perception and cognition and 3. to formalize them to be executable on a computational machinery. The outcome of the investigation is useful for designing visualizations for a given scenario or need, whose effectiveness can be quantified and thus the most understandable visualization design can be effortlessly determined. The science of visualization has already gained some understanding of structural visual abstraction. When for example illustrators, artists, and visualization designers convey certain structure, or visually express how things look, we can often provide a scientifically-founded argument whether and why is their expression effective for human cognitive processing. What has not been given sufficient scientific attention to, is advancing the understanding of procedural visual abstraction, in other words investigating visual means that convey what things do or how things work. This missing piece of knowledge would be very useful for visual depiction of processes and dynamics that are omnipresent in science, technology, but also in our everyday lives. The upcoming project will therefore investigate theoretical foundations for visualization of processes. Physiological processes that describe the complex machinery of biological life will be picked as a target scenario. The reason for this choice is two-fold. Firstly, these processes are immensely complex, are carried-out on various spatial and temporal levels simultaneously, and can be sufficiently understood only if all scales are considered. Secondly, physiological processes have been modeled as a result of intensive research in biology, systems biology, and biochemistry and are available in a form of digital data. The goal will be to visually communicate how physiological processes participate on life by considering the limitations of human perceptual and cognitive capabilities. By solving individual visualization problems of this challenging target scenario, the research will provide first pieces of understanding of procedural visual abstractions that are generally applicable, beyond the chosen target domain. Prototype implementation of the developed technology is available at the GitHub repository: https://github.com/illvisation/
\r\n\r\nPrototype implementation of the developed technology is available at the GitHub repository:
\r\nhttps://github.com/illvisation/
cellVIEW is a new tool that provides fast rendering of very large biological macromolecular scenes and is inspired by state-of-the-art computer graphics techniques. Click here for additional information.
\r\n\r\n18.11.2016: Arthur J. Olson, Envisioning the Visible Molecular Cell
\r\n17.10.2016: Kwan-Liu Ma, Emerging Topics for Visualization Research: Part1, Part2
\r\n07.10.2016: Marc Streit, From Visual Exploration to Storytelling and Back Again
\r\n04.12.2015: Jan Palacek, Visual Analysis of Protein Complexes: From Protein Interaction to Cellular Processes
\r\n19.04.2013: Jan Koenderink, Shape in Visual Awareness
Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "antes_sebastian-2026-msc", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "telaar_sina-2026-baa", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" }, { "id": "MedVis", "drupal_id": 4133, "name": "Medical Visualization", "short_abstract": "This research area bridges the gap between visualization and medicine by providing comprehensible visual means to detect diseased regions or to aid clinical treatment decisions.", "abstract": "In collaboration with hospitals we try to investigate various topics in medicine by means of visualization or visual analytics. Due to the increasing amount of data generated by hospital information systems, visualization becomes successively more important. Extracting certain trends from such highly diverse data by suitable visual mappings is one of the primary goals of medical visualization. The data is usually acquired by computed tomography, magnetic resonance imaging or ultrasound.\n\nCurrently, our research addresses the analysis of blood vessels such as the inspection of possible stenotic regions or their spatial arrangement as in the Circle of Willis. Furthermore, we investigate aneurysm classification and lesion detection as well as visualization. Another research area deals with realistic prenatal visualization of the fetus in-vivo and in real-time. Due to the high variability of medical imaging data, we further focus on high-level correction of segmentation defects.", "website": "https://www.cg.tuwien.ac.at/research/area/MedVis", "teaser": { "name": "teaser.png", "path": "research_area:MedVis", "type": "image/png", "size": 225330, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/MedVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "amabili2021", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "antes-2023-vhv", "arbesser_ba_2023", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Bauer_David_2018", "bayat-2022-mva", "Bernold_2019", "bernold-2019-epr", "Birkeland-2012-IMC", "borondy2022", "bront-2023-svo", "bruckner-2010-HVC", "burns-2007-fea", "Chen-Information-2016", "djuric-2020-wvo", "Eckelt_2017", "Eichner2022", "EuroVis2018-ShortPapers-Karall", "fmistelbauer-2014-adict", "Ford-2012-HRV", "furmanova_2020", "Gadllah_Hani_2016", "Gall_2017", "gall_alexander_2016BA", "ganglberger2019", "Gietl_2020", "Gillmann2021", "Groeller_2016_P4", "Groeller_V42020", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "gutekunst_2019", "Hainoun2019", "Heim-2017", "Ismail-2018", "jank-2022-cbf", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "Kovacs_PhD", "Machegger2018DTI", "magg-2021-dva", "magg2021", "magg2022", "malan_fluoro", "martorell2022", "Masopust_2018", "Mazza_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "mindek-2017-dsn", "Mistelbauer_2021", "Mistelbauer_Gabriel_2016", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "moerth_eric-2016-3DF", "moerth-2018-tpose", "Musleh_PhD", "musleh-2023-ugi", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "PERNDORFER-2015-ECS", "Pezenka-2016-MT", "Philipp_Hochhauser_2023", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_visgap2020", "raidou2018visualflatter", "Reiter2017CVAP", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "ruiz-2008-OVR", "ruiz-2008-SEV", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "Schmidlehner_Sandra_SbC", "Schrempf_2018", "schultes_lampi", "SifuentesGangl2017FIS", "solteszova-2010-MOS", "Solteszova2016", "Spelitz2020", "stritzel2022", "Stritzel2022_thesis", "Tramberger_2018", "Tramberger2017BCS", "unger_2017", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_HQ3", "Viola_Ivan_DAC", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "vitruvian_2019", "vogel2022", "Weissenboeck_2019_PhD" ], "projects": [ "d9951", "Smile Analytics" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=MedVis", "__class": "ResearchArea" } ], "keywords": [ "Circle of Willis", "medical visualization", "information visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 1900, "image_height": 1842, "name": "miao_2016_cgf-image.png", "type": "image/png", "size": 271848, "path": "Publication:miao_2016_cgf", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "miao_2016_cgf-paper.pdf", "type": "application/pdf", "size": 5537482, "path": "Publication:miao_2016_cgf", "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/miao_2016_cgf-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2016/miao_2016_cgf/", "__class": "Publication" }, { "id": "Miao_2015_VCBM", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "CoWRadar: Visual Quantification of the Circle of Willis in Stroke Patients", "date": "2015-09", "abstract": "This paper presents a method for the visual quantification of cerebral arteries, known as the Circle of Willis (CoW).\nThe CoW is an arterial structure that is responsible for the brain’s blood supply. Dysfunctions of this arterial circle\ncan lead to strokes. The diagnosis relies on the radiologist’s expertise and the software tools used. These tools\nconsist of very basic display methods of the volumetric data without support of advanced technologies in medical\nimage processing and visualization. The goal of this paper is to create an automated method for the standardized\ndescription of cerebral arteries in stroke patients in order to provide an overview of the CoW’s configuration. This novel display provides visual indications of problematic areas as well as straightforward comparisons between\nmultiple patients. Additionally, we offer a pipeline for extracting the CoW from Time-of-Flight Magnetic Resonance\nAngiography (TOF-MRA) data sets. An enumeration technique for the labeling of the arterial segments is therefore\nsuggested. We also propose a method for detecting the CoW’s main supplying arteries by analyzing the coronal,\nsagittal and transverse image planes of the data sets. We evaluated the feasibility of our visual quantification\napproach in a study of 63 TOF-MRA data sets and compared our findings to those of three radiologists. 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John", "isbn": "978-3-905674-82-8", "issn": "2070-5786", "lecturer": [ { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "gall_alexander_2016BA", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Miao_2015_VCBM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2018", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao2018Dimsum", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1263", "__class": "Author" } ], "location": "Chester, United Kingdom", "organization": "EG Digital Library", "pages_from": "1", "pages_to": "10", "publisher": "The Eurographics Association", "research_areas": [ { "id": "InfoVis", "drupal_id": 4128, "name": "Information Visualization and Visual Analytics", "short_abstract": "In this research area, our focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning. ", "abstract": "Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "antes_sebastian-2026-msc", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", 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"steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "telaar_sina-2026-baa", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" }, { "id": "MedVis", "drupal_id": 4133, "name": "Medical Visualization", "short_abstract": "This research area bridges the gap between visualization and medicine by providing comprehensible visual means to detect diseased regions or to aid clinical treatment decisions.", "abstract": "In collaboration with hospitals we try to investigate various topics in medicine by means of visualization or visual analytics. Due to the increasing amount of data generated by hospital information systems, visualization becomes successively more important. Extracting certain trends from such highly diverse data by suitable visual mappings is one of the primary goals of medical visualization. The data is usually acquired by computed tomography, magnetic resonance imaging or ultrasound.\n\nCurrently, our research addresses the analysis of blood vessels such as the inspection of possible stenotic regions or their spatial arrangement as in the Circle of Willis. Furthermore, we investigate aneurysm classification and lesion detection as well as visualization. Another research area deals with realistic prenatal visualization of the fetus in-vivo and in real-time. Due to the high variability of medical imaging data, we further focus on high-level correction of segmentation defects.", "website": "https://www.cg.tuwien.ac.at/research/area/MedVis", "teaser": { "name": "teaser.png", "path": "research_area:MedVis", "type": "image/png", "size": 225330, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/MedVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "amabili2021", "amirkhanov-2018-withteeth", "amirkhanov-2021-diss", "antes-2023-vhv", "arbesser_ba_2023", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2008-hvv", "Balabanian-2010-IIV", "Bauer_David_2018", "bayat-2022-mva", "Bernold_2019", "bernold-2019-epr", "Birkeland-2012-IMC", "borondy2022", "bront-2023-svo", "bruckner-2010-HVC", "burns-2007-fea", "Chen-Information-2016", "djuric-2020-wvo", "Eckelt_2017", "Eichner2022", "EuroVis2018-ShortPapers-Karall", "fmistelbauer-2014-adict", 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"SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", "weissenboeck-2014", "Wihann_2017", "wolf-2023-cc", "wolf-2024-jhd", "Woschizka_2021", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-tvcg", "wu-2021", "wu-2021-vi", "xmastree2002", "xmastree2005", "ymca", "YOGHOURDJIAN2019", "Zambal-2003-SWA", "zambal-2005-3dact", "Zaufel_2021", "zauner-2013-svkinect", "zechmeister2020", "Zeng_2021", "Zhu-2014-flowvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Workgroup&id=vis", "__class": "Workgroup" } ], "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_2015_VCBM/", "__class": "Publication" }, { "id": "Miao_Haichao_2015_VQC", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Visual Quantification of the Circle of Willis in Stroke Patients", "date": "2015-04", "abstract": "This thesis presents a novel method for the visual quantification of cerebral arteries. The Circle of Willis (CoW) is an arterial structure that is responsible for the brain’s blood supply. Dysfunctions of this arterial circle can lead to strokes. The diagnosis of stroke patients is complex\nand relies on the radiologist’s expertise and the software tools used. These tools consist of very basic display methods of the volumetric data without support of state-of-the-art technologies in medical image processing and visualization. The goal of this thesis is to create an automated\nmethod for the standardized visualization of cerebral arteries in stroke patients in order to allow visual indications of problematic areas as well as straightforward inter-patient comparisons.\n\nPrior to the visualization, this work offers a solution for the extraction of the CoW from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) images. An enumeration technique for the labeling of the segments is therefore suggested. Furthermore, it proposes a method for the detection of the CoW’s main supplying arteries by analyzing the coronal, sagittal and transverse image planes of the volume. This work gives a comprehensive account of the entire pipeline that is required to extract the arteries in the CoW and to build a model for the standardized\nvisualization. The final goal of this thesis is to create an effective display of the arteries based on a radial tree layout.\n\nThe feasibility of the visual quantification method is tested in a study of 63 TOF-MRAs. With the proposed methodology applied to the subjects, the results were compared to the findings from radiologists. The obtained results demonstrate that the proposed techniques are effective\nin detecting the arteries of the CoW. Finally, we focused our methods on the identification of the main arteries.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 552, "image_height": 470, "name": "Miao_Haichao_2015_VQC-.png", "type": "image/png", "size": 310337, "path": "Publication:Miao_Haichao_2015_VQC", "url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2015/Miao_Haichao_2015_VQC/Miao_Haichao_2015_VQC-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ { "id": 1263, "drupal_id": 863, "orcid_id": null, "website": "https://www.cg.tuwien.ac.at/staff/HaichaoMiao", "firstname": "Haichao", "lastname": "Miao", "searchname": "Haichao Miao", "is_teacher": false, "name": "Haichao Miao", "publications": [ "gadllah_2016", "gall_2016", "Halladjian_2020", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_stateKeylabTalk_2017", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Sarkis_2021", "Sbardellati-2019-vcbm", "wu-2019-report", "wu-2021", "wu-2021-vi" ], "publications_first": [], "project_leader": [], "publication_field": [ { "publ_id": "gall_alexander_2016BA", "field_id": "co_supervisor", "ordernum": 0 }, { "publ_id": "Miao_2015_VCBM", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2017", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao_tvcg_2018", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "miao2018Dimsum", "field_id": "lecturer", "ordernum": 0 }, { "publ_id": "sbardellati_ba_2018", "field_id": "supervisor", "ordernum": 1 } ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=Author&id=1263", "__class": "Author" } ], "matrikelnr": "0726810", "supervisor": [ { "id": 166, "drupal_id": 111, "orcid_id": "0000-0002-8569-4149", "website": "https://www.cg.tuwien.ac.at/staff/EduardGröller", "firstname": "Eduard", "lastname": "Gröller", "searchname": "Eduard Gröller", "is_teacher": true, "name": "Eduard Gröller", "publications": [ "a-2001-ah", "a-2001-ahr", "a-2001-Rec", "Acquisto-1995-DCR", "alacruzECR2004", "Alharbi_2021", "Alsallakh_2012_RCW", "amabili-2024-smg", "amabili-2025-lpb", "amirkhanov_2012", "amirkhanov_2012heur", "amirkhanov_2013_AMA", "amirkhanov-2011", "amirkhanov-2014-ama", "amirkhanov-2017-cffet", "amirkhanov-2018-withteeth", "amirkhanov-2019-manylands", "amirkhanov2010AMA", "amirkhanov2020visual", "Antonini2020", "Artner-2004-Hig", "Artner-2005-Hig", "Auzinger_Mistelbauer_2013_CSR", "balabanian-2007-ant", "balabanian-2008-hvv", "balabanian-2008-tst", "Balabanian-2010-IIV", 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"Groeller_2011_HP", "Groeller_2011_HSU", "Groeller_2011_IPV", "Groeller_2011_IVP", "Groeller_2011_NR", "Groeller_2011_NSM", "Groeller_2011_VCD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I1", "Groeller_2016_I2", "Groeller_2016_I3", "Groeller_2016_I4", "Groeller_2016_I5", "Groeller_2016_I6", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P3", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-1987-opt", "groeller-1988-duale", "groeller-1988-using", "groeller-1991-frac", "groeller-1991-temp", "groeller-1992-frac", "groeller-1992-fractals", "groeller-1992-fraktale", "groeller-1992-vis", "groeller-1993-acc", "groeller-1993-cha", "groeller-1993-coh", "groeller-1993-coh1", "groeller-1993-daten", "groeller-1993-dist", "groeller-1993-disto", "groeller-1993-eff", "groeller-1993-exp", "groeller-1993-frak", "groeller-1993-grund", "groeller-1993-oct", "Groeller-1994-AIV", "groeller-1994-appl", "Groeller-1994-AVT", "groeller-1994-coh", "Groeller-1994-CSA", "groeller-1994-ext", "Groeller-1994-HIS", "groeller-1994-hyper", "Groeller-1994-IDN", "groeller-1994-int", "Groeller-1994-ITV", "groeller-1994-mod", "Groeller-1994-MRN", "groeller-1994-tech", "groeller-1994-vis", "groeller-1995-appl", "groeller-1995-attract", "Groeller-1995-CCG", "groeller-1995-dyn", "Groeller-1995-GOW", 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", "abstract": "Data and information created by various processes (e.g., simulations) is getting larger, and more and more complex. We use interactive visualization and analysis techniques to facilitate exploration of complex parameter spaces (e.g., to analyze and compare parameters for automotive engineering, reconstruction algorithms, or geometry generators) or unstructured information collections (e.g., annotated digital documents or image collections). Our research focus lies on novel visual encodings and interaction techniques to explore a large amount of abstract data, often in combination with analytical reasoning.
\r\n", "website": "https://www.cg.tuwien.ac.at/research/area/InfoVis", "teaser": { "name": "teaser.png", "path": "research_area:InfoVis", "type": "image/png", "size": 60875, "orig_name": "teaser.png", "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/research_area/InfoVis/teaser:thumb{{size}}.png", "thumb_image_sizes": [ 64, 120, 300 ] }, "workgroups": [ "vis" ], "publications": [ "8564188", "antes_sebastian-2026-msc", "arbesser_ba_2023", "Arleo-2019-vis", "Batik-2021", "batik-2021-gd", "bayat-2022-mva", "beham-2014-cupid", "bhore-2021-issac", "birsak-2014-agtb", "birsak-2017-dpe", "borgo-2013-gly", "borondy2022", "Braunsperger-2025_bsc", "Bruckner_Stefan_2015_VAS", "bugnar-esk-2021", "byska-2019-mdfc", "Cai_2018", "casellato-2016-pkg", "Chen-Information-2016", "cizmic-2018-evd", "cmolik-2020-tvcg", "Cornel_2020", "daae-lampe-2010-dif", "Deutsch-2018", "Diehl_2015", "Diehl_2021", "dworschak-2016-szcm", "Eckelt_2018_01", "edlinger-2018-vwr", "ehlers-2024-vgs", "eichner-2024-erv", "eitler-2024-sos", "eiweck-hnv-2021", "ellhotka-2025-ipo", "eschner-2023-evl", "eschner-2025-ide", "Escribano_2017", "fourousan2021", "furmanova_2020", "Gadllah_Hani_2016", "Gall2020", "Ganuza_ML_2015_ISA", "georgiev-2019-cbg", "geyer_lukas_2015_prj", "geymayer-2017-std", "Groeller_2011_CW", "Groeller_2011_NR", "Groeller_2014_RWA", "Groeller_2016_P1", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2021-10", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V5_2020", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "gundacker-2020-wlm", "gusenbauer-2018", "gusenbauer-2018-P", "Heim_2021", "heim-2024-accustripes", "heim-gall-2020-dde", "Heinzl2021", "holzer-edo", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "karnik-09-shapegrammar", "Kehrer-2010-mom", "kehrer-2012-mod", "kehrer-2013-SBC", "Kehrer-2013-STAR", "klaffenboeck-2024-rva", "klaffenboeck-thesis", "Klein_Tobias_2015TIV", "klein-2016-WCL", "knoetzl_alexander-2025-prj", "koeppel-2021", "Kolter_2021", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch-2021-lov", "Kuroko-2020-iV", "Laschober-2018", "li-2019-gdc", "lippeck-2022-mna", "louis-alexandre_dit_petit-frere-2022-veo", "magg2022", "mahler-2021-mdar", "martorell2022", "maruyama-2019-iv", "Matkovic_Kresimir_2015_", "Matkovic-2014-ieee", "matt-2024-cvil", "matt-2025-scv", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "medeiros-2023-gwf", "meka-2024-lpi", "melcher-2024-asi", "Miao_2015_VCBM", "miao_2016_cgf", "Miao_Haichao_2015_VQC", "miao2018Dimsum", "mizuno-2019-eurovis", "Muehlbacher_diss_2018", "musleh_maath_2021_mam", "musleh_maath-2021-mam1", "musleh_maath-2021-mam2", "Musleh_PhD", "musleh-2022-mam5", "musleh-2025-trustme", "Neubauer2020", "Nowak_2021", "ortner-2016-tunnel", "ortner-2016-visaware", "pahr-2024-ieo", "PH-2011-LDS", "Pilizar_-2020-bachelor", "pirch_2021_VRN", "pointner_simon-2020", "polatsek-2018-stv", "Presch_2020", "Priselac2021", "Purchase-2020-gd", "Purgathofer-2017-China1", "Purgathofer-2017-China2", "Purgathofer-2017-VC-Interface", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_bestphd", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2019_prsps", "Ribicic_2012_VAS", "Rippberger_2019", "rozana-2026-vcfd", "sakr_sherif-2020-cacm", "samoul-2019-cnp", "sbardellati-2021-eveos", "schmidt-phd", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sikachev_peter-2011-protovis", "smiech-2018-tei", "sMolBoxes_2022", "Sorger_2013_nMI", "sorger-2013-neuromap", "sorger-2015-litevis", "sorger-2015-taxintec", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "spegel-gruenberger-2020", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "steinschorn-2025-parameter", "stoff-2025-pvu", "stoff-concepMap-2021", "stritzel2022", "Strohmayer-2018-BT", "takahashi-2019-acdt", "tekaya-2025-amo", "telaar_sina-2026-baa", "Thomas-2018", "TR1862162", "Troidl_2019", "turner-aso", "unger-2019_vcp", "vad_viktor-2017-WVE", "vaico", "Vasileva-2018", "vasileva-2019-smw", "Wagner_032017", "wagner-2024-par", "walchhofer_ar_flowmaps", "waldin-2019-ccm", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "webGPU_aggregateVis-2023", "wolf-2023-cc", "wolf-2024-jhd", "wu-2017-dagstuhl", "wu-2018-JVLC", "wu-2018-metabo", "wu-2018-shonan", "wu-2018-story", "wu-2019-bmc", "wu-2019-report", "wu-2019-smw", "wu-2019-smwp", "wu-2019-vcbm", "wu-2019-visworkshop", "wu-2020-eurovis-star", "wu-2020-tvcg", "ymca", "YOGHOURDJIAN2019" ], "projects": [ "BioNetIllustration", "d10206", "d10413", "d10450", "d9282", "d9522", "d9555", "deskollage", "Scenario Pool" ], "url": "https://www.cg.tuwien.ac.at/research/publications/show.php?class=ResearchArea&id=InfoVis", "__class": "ResearchArea" }, { "id": "MedVis", "drupal_id": 4133, "name": "Medical Visualization", "short_abstract": "This research area bridges the gap between visualization and medicine by providing comprehensible visual means to detect diseased regions or to aid clinical treatment decisions.", "abstract": "In collaboration with hospitals we try to investigate various topics in medicine by means of visualization or visual analytics. Due to the increasing amount of data generated by hospital information systems, visualization becomes successively more important. Extracting certain trends from such highly diverse data by suitable visual mappings is one of the primary goals of medical visualization. The data is usually acquired by computed tomography, magnetic resonance imaging or ultrasound.\n\nCurrently, our research addresses the analysis of blood vessels such as the inspection of possible stenotic regions or their spatial arrangement as in the Circle of Willis. Furthermore, we investigate aneurysm classification and lesion detection as well as visualization. Another research area deals with realistic prenatal visualization of the fetus in-vivo and in real-time. 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"Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSD", "Groeller_2011_VSS", "Groeller_2012_KAV", "Groeller_2012_VBP", "Groeller_2012_ViV", "Groeller_2012_VV", "Groeller_2014_CaQ", "Groeller_2014_CQV", "Groeller_2014_CV", "Groeller_2014_RWA", "Groeller_2014_STC", "Groeller_2014_UPS", "Groeller_2014_VND", "Groeller_2016_I2", "Groeller_2016_I7", "Groeller_2016_I8", "Groeller_2016_P2", "Groeller_2016_P4", "Groeller_2016_P6", "Groeller_2016_P7", "Groeller_2021_11", "Groeller_2021_BVM", "Groeller_2021-10", "Groeller_Edi_2013_TVC", "Groeller_Edi_2013_VCQ", "Groeller_Edi_2013TVCK", "Groeller_Edi_VKA", "Groeller_Eduard_2014_THS", "Groeller_Eduard_2014_TSP", "Groeller_Eduard_2014_UCT", "Groeller_Eduard_2015_SMV", "Groeller_Eduard_2015_TCU", "Groeller_V1_2020", "Groeller_V2_2020", "Groeller_V3_2020", "Groeller_V42020", "Groeller_V5_2020", "groeller-2004-efficient", "groeller-2004-imp", "groeller-2004-sci", "groeller-2005-dia", "Groeller-2010-CVC", "Groeller-2010-IFI", "Groeller-2010-IVVI", "Groeller-2011-HSH", "Groeller-2017-ARTORW", "Groeller-2017-AVC", "Groeller-2017-IVAMCS", "Groeller-2017-PTPMD", "Groller_2021-12-03", "Gronde_2008", "Grorller-2010-IVV", "grossmann_2019_pelvisrunner_poster", "Grossmann_MA", "grossmann-2021-layout", "grossmann-2022-conceptSplatters", "grossmann-thesis", "gruber-2025-vps", "Gruenauer-2011-CAT", "Gschwantner_2011_AMQ", "gundacker-2020-wlm", "Gurbat_2011_SBS", "gusenbauer-2018", "gusenbauer-2018", "gusenbauer-2018-P", "gutekunst_2019", "Hadwiger-2002-Fas", "haidacher_2010_statTF", "haidacher-2004-FVV", "haidacher-2005-MND", "haidacher-2007-idr", "haidacher-2008-vcbm", "haidacher-2011-MSM", "haidacher-2011-phd", "haidacher-2011-VAM", "Hainoun2019", "Halladjian_2020", "hanzl-2011", "hartl-2008-vcd", "hartmann-2005-adv", "haushofer-2018-skinning", "Heim_2020", "Heim_2021", "Heim-2017", "heim-2024-accustripes", "heim-gall-2020-dde", "heinzl_2006_RSDVCDM", "heinzl-2006-rep", "heinzl-2008-sam", "Heinzl2021", "Herghelegiu-2012-BPV", "herzberger-2023-swv", "herzberger-2024-roh", "Hirsch_Christian_2015_ABL", "Hladuvka-2002-Exp", "hladuvka-2002-exploiting", "Hochmayr_Manuel_2015_PSE", "hochmayr_manuel-2011-VoRMD", "Hochpoechler_2016_VR", "horvath-2018-ism", "hromniak-2019-vcn", "huber-2025-eed", "Iijima-2020-iV", "indirectBiasLanguageModels-2023", "irendorfer-2024-uat", "irger-2023-ves", "Ismail-2018", "jank-2022-cbf", "Kanitsar-2002-CPR", "Kanitsar-2003-Adva", "Kanitsar-2003-Dem", "Kanitsar-2004-Dia", "Kanitsar-thesis", "kapferer-2017-godot", "Karall2017CVAB", "Karall2018_2", "karimov-2013-vivisection", "karimov-2015-HD", "karimov-2016-GIVE", "karimov-2016-SD", "keglevic_schulz-2011-MB", "Kehrer-2008-hyp", "Kehrer-2010-mom", "kehrer-2011-vai", "kehrer-2012-mod", "kehrer-2013-IVA", "kehrer-2013-SBC", "Kehrer-2013-STAR", "Kehrer-2014-CSD", "kerbl-2024-ah3", "kimmersdorfer-fancyMaps-2023", "Kinkelin_2009", "Kinkelin-2011-VR", "Klaus2024", "Kleber-2004-TFE", "klein_2017_IM", "klein_2019_MSA_Poster", "klein_2019_PGG", "klein_2019_PHD", "klein_2019_PMP", "Klein_Tobias_2015TIV", "klein-thesis", "Knapp_2017_CVR", "knapp_michael_2004_MAS", "knapp-2004-semi", "koch_bernhard_2018-1", "koch-2018-sso", "koehle-2013-sgv", "koeppel-2021", "Koeppel2020", "Kohlmann-2007-EBV", "kohlmann-2007-livesync", "kohlmann-2008-lse", "kohlmann-2009-cp", "kohlmann-2009-lssl", "kolesar-ivan-2014-polymers", "Kolter_2021", "komon-2025-dco", "komon-2025-webigeo", "komon-2025-webigeo", "komon-kimmersdorfer-2025-weBIGeo", "Konyha_2013_IVA", "korpitsch_thorsten-2019", "korpitsch-2020-cescg", "Korpitsch-2020-wscg", "korpitsch-2021-lov", "Koszticsak-2017-ewt", "Kouril_2017_11", "kouril-2015-maya2cellview", "kouril-2017-sccgposter", "kouril-2018-LoL", "kouril-2018-LoL", "kouril-2020-hyperlabels", "kouril-2021-molecumentary", "kouril-2021-phdthesis", "Kovacs_PhD", "krakhofer-2015", "Krone2016VABC", "kuehschelm-2005-adv", "Kugler_2019", "Kuroko-2020-iV", "Labschuetz_Matthias_2015_JIT", "Labschuetz_Matthias_2016_AHD", "Labschuetz_Matthias_2016_JIT", "Labschuetz_Matthias_2016_JITT", "Lackner_2022", "LaCruz2004", "Ladstaedter-2009-sim", "Langer_Edith_IR1", "Langer_Maximillian_DMV", "Laschober-2018", "lawonn-2018-illvisstar", "lemuzic_2014_ipv", "lemuzic_2015_timelapse", "LeMuzic_2016_PhD", "lemuzic-2014-ivm", "lemuzic-2015-hiv", "lemuzic-mindek-2016-viseq", "lemuzic-mindek-sorger-cgfcc", "Leutschacher_2022", "li-2019-gdc", "lie-2009-cri", "lipp-2017-mgpu", "lipp-2017-vulkan", "lippeck-2022-mna", "liu-2014-ac", "lkoell-2014", "ludwig-2012-MT", "Machegger2018DTI", "magg-2021-dva", "magg2021", "mahler-2021-mdar", "major-2010-mrf", "malan_fluoro", "malik-2007-FP", "malik-2009-CVFA", "malik-thesis", "Manczarski-2016", "Marek06", "Maricic_2013_VFE", "martorell2022", "maruyama-2019-iv", "Masopust_2018", "Masterthesis-Viola", "Matkovic_Kresimir_2015_", "matt-2023-vae", "matt-2024-cvil", "matt-2025-scv", "matt-masterthesis", "Mattausch-2003-ISL", "Mattausch-2003-SIE", "Mattausch-2003-Str", "Matusich-2017-01", "Mautner 2020", "Mayr-2017-1", "mayr-2021-wec", "mazurek-2017-sio", "mazurek-2017-vows", "mazurek-2018-vac", "mazurek-2018-veq", "Mazza_2020", "Mazza_2021_05", "meka-2024-lpi", "Melo_2018_11", "Meusburger_2020", "Miao_2015_VCBM", "Miao_2019", "Miao_Haichao_2015_VQC", "miao_inria_2017", "miao_kaust_2018", "miao_nantech_2019", "miao_nar_2020", "miao_plitvice_2018", "miao_thesis_2019", "miao_tvcg_2017", "miao_tvcg_2018", "miao_tvcg_2018", "miao_tvcg_2018", "miao2018Dimsum", "Miao2018FDN", "Michl_2017_CSV", "mindek_peter-2012-visgroupproj", "mindek_peter-2014-cs_kaust", "mindek-2013-cs_cvut", "mindek-2013-csl", "mindek-2013-pel", "mindek-2014-mcs", "mindek-2014-vivi_cvut", "mindek-2015-mc", "mindek-2015-mctalk", "mindek-2016-utah-talk", "mindek-2017-dsn", "mindek-2017-marion", "mindek-2017-virtualcell", "mindek-2018-fyi", "mindek-2019-mci", "mindek-thesis", "mistelbauer_2013_SIV", "Mistelbauer_2021", "Mistelbauer_Gabriel_2015_NHR", "Mistelbauer_Gabriel_2016", "mistelbauer-2010-pvv", "mistelbauer-2012-cr", "mistelbauer-2012-ssv", "mistelbauer-2013-cfa", "mistelbauer-2015-abvv", "Mitterhofer_2017", "mizuno-2019-eurovis", "Mlejnek_2004_PF", "Mlejnek_2005_AOEPF", "Mlejnek_2006_MVOA", "Mlejnek-2004-Int", "Mlejnek-2004-ITVAC", "Mlinaric-2015-MT", "Moellinger_Christian_IDE2", "moerth_eric-2016-3DF", "moerth-2018-tpose", "monitzer_2008_FluSi", "Morar_2012_ISB", "Muehlbacher_diss_2018", "mueller-2009-ivs", "Muigg_2011_ISI", "Muigg_2011_VC", "Muigg-2008-four", "muigg-2012-svr", "musleh-2024-conan", "muth-2026-clouds", "Neumann-2002-Fea", "nguyen_2020-covid", "Niedermayer_2018", "Novotny_2013_ASVD", "Nowak_2020", "Nowak_2021", "Oancea_2018_1", "Oancea_Stefan_2016_VOT", "Oancea2018OAK", "oeltze-2013-tut", "opitz-2009-cvv", "Ortner_PhD", "Ortner2020", "Pahr_PhD", "pahr-2021-vologram", "pahr-2024-ieo", "pahr-2024-squishicalization", "pahr-2025-holographs", "pahr-2025-nodkant", "Pahr2020", "Pajer_2012_VoM", "Panayotov", "papantonakis-2024-rmf", "Parzer_2013_IIG", "patel_2009_MC", "patel_daniel_2007_IRSD", "patel-2008-tsa", "patel-2009-evr", "patel-2011-PEA", "Pauschenwein_2022", "Peter_2012_AIV", "Pezenka-2016-MT", "Pfahler_David_2015_IPI", "Pfahler-2016-MT", "PH-2011-LDS", "phd-viola", "Philipp_Hochhauser_2023", "Pilizar_-2020-bachelor", "piringer-2009-hds", "Plank_Pascal_2015_HVP", "plank-2017-sldg", "PMI_AR_2012", "pointner_simon-2020", "polatsek-2018-stv", "polatsek-2018-stv", "Pramerdorfer-2011-PAV", "preim-2009-sve", "Presch_2020", "Priselac2021", "puehringer-2009-sbm", "puenguentzky-2014-ht", "Purchase-2020-gd", "raidou_2018_bladderrunner", "raidou_2019_pelvisrunner", "raidou_2019_preha", "raidou_2019_springer", "raidou_2020Onc", "raidou_EuroVis15", "raidou_eurovis16", "raidou_miccai16", "raidou_pingu2020", "raidou_previs2021", "raidou_RO2019", "raidou_shonan167", "raidou_slicedice", "raidou_star2019", "raidou_vcbm14", "raidou_vis14", "raidou_vis15", "raidou_visgap2020", "raidou2018_rv3", "raidou2018visualflatter", "raidou2019_prsps", "rasch-2016-imgses", "Rau08", "Rautek_Peter_2014_TUC", "Rautek_Peter_2014_VSA", "rautek-2005-dvr", "Rautek-2007-O3D", "Rautek-2007-SLI", "Rautek-2008-IDS", "Rautek-2008-kav", "Rautek-2008-VF", "rautek-2009-vmv", "RAUTEK06", "Rautek06Vis", "Rautek06VMLS", "rautek2010", "Red_Andreas_2015_FFT", "Reh_Andreas_VoP", "reh-2013", "reina-2020-mtv", "Reisacher_Matthias_CPW", "Reisacher2016", "Reiter_2009_IXIA", "Reiter2017CVAP", "Rezk06Vis", "Ribicic_2012_SUS", "Ribicic_2012_VAS", "Ribicic-2010-CRS", "Riegelnegg_2019", "rinortner_susanne-2019-vpicc", "rinortner_susanne-2019-vpicc", "Rippberger_2019", "rippl-2023-atg", "ritzberger-2010-nar", "Ropinski-2012-UBT", "rozana-2026-vcfd", "rraidou_clinical", "rraidou_EG17", "rraidou_phdbook", "rsabin-2013", "ruiz-2008-OVR", "ruiz-2008-SEV", "samoul-2019-cnp", "Sanjin_Rados_RV", "Sarkis_2021", "Sbardellati-2019-vcbm", "Sbardellati-2019-vcbm", "sbardellati-2021-eveos", "scharsach-2005-adv", "Schernthaner-2017-MCP", "schindler_2020vis", "Schindler-2022-eurovis", "schindler2020", "schleicher-2011-VLSC", "Schmidlehner_Sandra_SbC", "schmidlehner2021", "schmidt-2011-mt", "schmidt-phd", "schmidt-phd", "schoellhuber-2008-asc", "scholz_2021", "Schrempf_2018", "Schrempf_2020", "SCHUETZ-2024-SIMLOD", "schuetz-2025-splatshop", "schuh-2018-mesh-blending", "schultes_lampi", "Schulze_Florian_2013_CMI", "schwankl-2013-smis", "seyfert-2017", "shakhova-2023-atp", "sietzen-2019-wnn", "sietzen-2019-wnn", "sietzen-2021-perturber", "sietzen-2022-vacnnr", "sietzen-ifv-2019", "sifuentes-2018-crowd", "SifuentesGangl2017FIS", "sikachev_peter_2010_STLCI", "sikachev_peter-2011-dfc", "sikachev_peter-2011-incshad", "sikachev_peter-2011-metavis", "sikachev_peter-2011-protovis", "sikachev-2010-DFC", "sikachev-2010-ill_vis_vol_ren", "Sippl_Sebastian_EFG", "smiech-2018-tei", "Smisek_Michal_A3D", "Sollboeck_2011_FSS", "sollboeck-2011", "Solteszova-2009-VQN", "solteszova-2010-MOS", "Solteszova2016", "Sorger_2013_nMI", "sorger_2017_metamorphers", "sorger-2016-fowardabstraction", "sorger-2017-thesis", "sorger-2019-odn", "sorger-2021-egonet", "Soros_AVN_2011", "Soros-AV-2010", "Spechtenhauser_Florian_2016", "spegel-gruenberger-2020", "Spelitz2020", "spoerk-2010-hpgpu", "Stabel_2012_UDM", "stappen_2017_animatedcomic", "Staudacher_2022", "staudacher_florian-2016-topo3d", "stehno-2011-RVD", "steinboeck-2017-vbn", "steinboeck-2017-vefp", "steinboeck-2017-vefp", "steinboeck-2018-lbg", "STEINLECHNER-2019-ICT", "StickmanMax-shoetta-kampfer", "stoff-2025-pvu", "stoff-concepMap-2021", "StrakaVis2004", "stritzel2022", "Strohmayer-2018-BT", "sturl_2016_dynlabels", "suntinger-2008-etet", "suntinger-2008-tet", "Swoboda_Nicolas_VIT", "Swoboda2020", "szabo_patrik-2022-tour", "szabo-thesis", "takahashi-2019-acdt", "tekaya-2025-amo", "tekaya-2025-amo", "termeer-2006-000", "termeer-2007-covicad", "termeer-2008-scmr", "termeer-2008-vis", "termeer-2009-cvc", "termeer-2009-scmr", "textures-3d-printing", "thesis-kronsteiner", "thesis-tekaya", "Thomas-2018", "Thurner-2005-IVR", "toth-2007-ndd", "TR-186-2-05-01", "TR-186-2-05-02", "TR-186-2-05-03", "TR-186-2-05-04", "TR-186-2-05-06", "TR-186-2-05-07", "TR-186-2-05-08", "TR-186-2-06-01", "TR-186-2-06-02", "TR-186-2-06-03", "TR-186-2-06-04", "TR-186-2-07-02", "TR-186-2-07-03", "TR-186-2-07-04", "TR-186-2-07-05", "TR-186-2-07-06", "TR-186-2-07-07", "TR-186-2-07-08", "TR-186-2-07-10", "TR-186-2-07-11", "TR-186-2-07-12", "TR-186-2-08-01", "TR-186-2-08-02", "TR-186-2-08-03", "TR-186-2-08-04", "TR-186-2-08-05", "TR-186-2-08-06", "TR-186-2-08-07", "TR-186-2-08-08", "TR-186-2-08-10", "TR-186-2-08-11", "TR-186-2-08-12", "TR-186-2-08-14", "TR-186-2-09-01", "TR-186-2-15-03", "TR1862162", "Tramberger_2018", "Tramberger2017BCS", "Trautner_Thomas_2014_VAE", "trautner-2018-imd", "trautner-2018-imd", "travnicek-2017-thm", "Trenkwalder-2004-MAR", "tretyak-2025-tacmedvr", "Troidl_2019", "Troidl_2021", "Troidl_2022", "turner-aso", "tut-eg-2006", "tut-siggraph-2006", "tut-vis-2006", "tut-vis-2007", "tweebo-2014", "ulschmid-2024-reo", "ulschmid-2025-apc", "unger_2017", "unger-2019_vcp", "Unger2020", "unterguggenberger-2024-fropo", "usul-thesis", "vad_2015_phd", "Vad_Viktor_2015_RVV", "vad-2016-bre", "vaico", "varchola_andrej-2012-fetoscopic", "Vasileva_2022", "Vasileva-2018", "vessel2003", "Viola_2013_IDV", "Viola_Ivan_2013_CAI", "Viola_Ivan_2013_D3D", "Viola_Ivan_2013_DC", "Viola_Ivan_2013_GS", "Viola_Ivan_2013_HQ3", "Viola_Ivan_2013_RMA", "Viola_Ivan_2013_RSb", "Viola_Ivan_2013_SVA", "Viola_Ivan_2013_VCA", "Viola_Ivan_2015_AAM", "Viola_Ivan_2015_MCT", "Viola_Ivan_2015_VBS", "Viola_Ivan_CLD", "Viola_Ivan_DAC", "Viola_Ivan_IIP", "Viola_Ivan_UVP", "Viola_Ivan_VDP", "Viola-05-Smart", "Viola-2003-GPU", "Viola-2003-Har", "viola-2003-hbn", "Viola-2003-NON", "viola-2004-gbf", "Viola-2004-GPU", "viola-2004-har", "viola-2004-har2", "viola-2004-idv", "viola-2004-imp", "Viola-2004-ImpX", "Viola-2004-ImpX2", "viola-2005-imp", "viola-2006-FoA", "viola-evr", "Viola-Pondering-2017", "viola-popular-article-2006", "Viola-vistutillustrativevis", "vis-foa", "VisWeek-Tutorial-2012-Uncertainty", "vitruvian_2019", "voglreiter-2023-tro", "Vucenovic_2022", "vucini_2006", "vucini_2008_rnp", "vucini_2009", "vucini_erald-2007-FRI", "vucini-2009-phd", "vucini-2011", "Wagner_032017", "walchhofer_ar_flowmaps", "walchhofer-tso", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2016_Chameleon", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "Waldin_Nicholas_2017_FlickerObserver", "waldin-2017-thesis", "waldin-2019-ccm", "waldin-2019-ccm", "Waldner_2017_11", "Waldner_2017_11", "waldner-2013-facetCloudsGI", "waldner-2013-ubiWM", "waldner-2014-af", "waldner-2014-ghi", "waldner-2017-vph", "waldner-2018-ved", "waldner-2019-rld", "waldner-2020-tbg", "waldner-2021-leo", "waser_2011_VSD", "Waser-2010-WL", "webGPU_aggregateVis-2023", "weiner_2011", "Weissenboeck_2019", "Weissenboeck_2019_PhD", 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