[ { "id": "haidacher-2011-VAM", "type_id": "journalpaper", "tu_id": null, "repositum_id": null, "title": "Volume Analysis Using Multimodal Surface Similarity", "date": "2011-10", "abstract": "The combination of volume data acquired by multiple modalities has been recognized as an important but challenging\r\ntask. Modalities often differ in the structures they can delineate and their joint information can be used to extend the classification\r\nspace. However, they frequently exhibit differing types of artifacts which makes the process of exploiting the additional information\r\nnon-trivial. In this paper, we present a framework based on an information-theoretic measure of isosurface similarity between different\r\nmodalities to overcome these problems. The resulting similarity space provides a concise overview of the differences between the\r\ntwo modalities, and also serves as the basis for an improved selection of features. Multimodal classification is expressed in terms of\r\nsimilarities and dissimilarities between the isosurfaces of individual modalities, instead of data value combinations. We demonstrate\r\nthat our approach can be used to robustly extract features in applications such as dual energy computed tomography of parts in\r\nindustrial manufacturing.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Dual-energy CT data visualized using multimodal similarity-based classification", "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1500, "image_height": 1417, "name": "haidacher-2011-VAM-Teaser.jpg", "type": "image/jpeg", "size": 418896, "path": "Publication:haidacher-2011-VAM", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Teaser:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 597, 161, 166 ], "date_from": "2011-10-23", "date_to": "2011-10-28", "event": "IEEE Visualization 2011", "journal": "IEEE Transactions on Visualization and Computer Graphics", "lecturer": [ 597 ], "location": "Providence, Rhode Island, USA", "number": "12", "pages_from": "1969", "pages_to": "1978", "volume": "17", "research_areas": [], "keywords": [ "surface similarity", "volume visualization", "multimodal data" ], "weblinks": [], "files": [ { "description": "Video of the Fast Forward Presentation", "filetitle": "FastForward", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1280, "preview_image_height": 720, "name": "haidacher-2011-VAM-FastForward.avi", "type": "video/x-msvideo", "size": 2962030, "path": "Publication:haidacher-2011-VAM", "preview_name": "haidacher-2011-VAM-FastForward:preview.png", "preview_type": "image/jpeg", "preview_size": 33557, "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-FastForward.avi", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-FastForward:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-FastForward:video.mp4" }, { "description": "", "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "haidacher-2011-VAM-Paper.pdf", "type": "application/pdf", "size": 15432630, "path": "Publication:haidacher-2011-VAM", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Paper:thumb{{size}}.png" }, { "description": "VisWeek 2011 Presentation Slides", "filetitle": "Presentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "haidacher-2011-VAM-Presentation.pdf", "type": "application/pdf", "size": 12638148, "path": "Publication:haidacher-2011-VAM", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Presentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Presentation:thumb{{size}}.png" }, { "description": "Dual-energy CT data visualized using multimodal similarity-based classification", "filetitle": "Teaser", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1500, "image_height": 1417, "name": "haidacher-2011-VAM-Teaser.jpg", "type": "image/jpeg", "size": 418896, "path": "Publication:haidacher-2011-VAM", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Teaser.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Teaser:thumb{{size}}.png" }, { "description": "Video demonstration of some of the key aspects of our approach", "filetitle": "Video", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1024, "preview_image_height": 912, "name": "haidacher-2011-VAM-Video.avi", "type": "video/x-msvideo", "size": 42124998, "path": "Publication:haidacher-2011-VAM", "preview_name": "haidacher-2011-VAM-Video:preview.png", "preview_type": "image/jpeg", "preview_size": 44314, "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Video.avi", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/haidacher-2011-VAM-Video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-VAM/", "__class": "Publication" }, { "id": "haidacher-2011-phd", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "Information-based Feature Enhancement in Scientific Visualization", "date": "2011", "abstract": "Scientific visualization is a research area which gives insight into volumetric data acquired through measurement or simulation. The visualization allows a faster and more intuitive exploration of the data.\r\n\r\nDue to the rapid development in hardware for the measurement and simulation of scientific data, the size and complexity of data is constantly increasing. This has the benefit that it is possible to get a more accurate insight into the measured or simulated phenomena. A drawback of the increasing data size and complexity is the problem of generating an expressive representation of the data.\r\n\r\nSince only certain parts of the data are necessary to make a decision, it is possible to mask parts of the data along the visualization pipeline to enhance only those parts which are important in the visualization. For the masking various properties are extracted from the data which are used to classify a part as important or not. In general a transfer function is used for this classification process which has to be designed by the user.\r\n\r\nIn this thesis three novel approaches are presented which use methods from information theory and statistics to enhance features from the data in the classification process that are important for a certain task. With the tools of information theory and statistics it is possible to extract properties from the data which are able to classify different materials or tissues in the data better than comparable other approaches.\r\n\r\nOne approach adaptively extracts statistical properties, i.e. the mean value and the standard deviation, of the data values in the local neighborhood of each point in the data set. With these statistical properties it is possible to better distinguish between different materials in a data set even though the data is very noisy.\r\n\r\nThe other two approaches in this thesis employ methods from information theory to extract features from multimodal data sets. Thus it is possible to enhance features of the data which are either very similar or very dissimilar in both modalities. Through information theory the variations in the value ranges of both modalities do not influence the classification of these features.\r\n\r\nAll three approaches define novel transfer-function spaces which simplify the design process of a transfer function for the user. Different features of the data, such as different materials, can be clearly depicted in these spaces. Therefore, it is easier for a user to design a transfer function which enhances the features of importance for a certain task.\r\n\r\nFor each of the new approaches results and comparisons to other existing techniques are shown to highlight the usefulness of the proposed methods. Through the described research it is shown that information theory and statistics are tools which are able to extract expressive properties from the data.\r\n\r\nIn the introduction a broad overview over scientific visualization and the visualization pipeline is given. The classification process is described in more detail. Since information theory and statistics play an important role for all three approaches, a brief introduction to these concepts is given as well.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2486, "image_height": 2530, "name": "haidacher-2011-phd-Image.png", "type": "image/png", "size": 3039441, "path": "Publication:haidacher-2011-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/haidacher-2011-phd-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/haidacher-2011-phd-Image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 597 ], "date_end": "2011-06", "date_start": "2007-10", "reviewer_1": [ 166 ], "reviewer_2": [ 951 ], "rigorosum": "2011-06-17", "supervisor": [ 166 ], "research_areas": [], "keywords": [ "Scientific visualization", "Information theory", "Volume classification" ], "weblinks": [], "files": [ { "description": "", "filetitle": "Image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 2486, "image_height": 2530, "name": "haidacher-2011-phd-Image.png", "type": "image/png", "size": 3039441, "path": "Publication:haidacher-2011-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/haidacher-2011-phd-Image.png", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/haidacher-2011-phd-Image:thumb{{size}}.png" }, { "description": "", "filetitle": "PhD Thesis", "main_file": true, "use_in_gallery": false, "access": "public", "name": "haidacher-2011-phd-PhD Thesis.pdf", "type": "application/pdf", "size": 16173886, "path": "Publication:haidacher-2011-phd", "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/haidacher-2011-phd-PhD Thesis.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/haidacher-2011-phd-PhD Thesis:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2011/haidacher-2011-phd/", "__class": "Publication" }, { "id": "haidacher_2010_statTF", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Volume Visualization based on Statistical Transfer-Function Spaces", "date": "2010-03", "abstract": "It is a difficult task to design transfer functions for noisy data. In traditional transfer-function spaces, data values of different materials overlap. In this paper we introduce a novel statistical transfer-function space which in the presence of noise, separates different materials in volume data sets. Our method adaptively estimates statistical properties, i.e. the mean value and the standard deviation, of the data values in the neighborhood of each sample point. These properties are used to define a transfer-function space which enables the distinction of different materials. Additionally, we present a novel approach for interacting with our new transfer-function space which enables the design of transfer functions based on statistical properties. Furthermore, we demonstrate that statistical information can be applied to enhance visual appearance in the rendering process. We compare the new method with 1D, 2D, and LH transfer functions to demonstrate its usefulness.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "Brain classification", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1050, "image_height": 947, "name": "haidacher_2010_statTF-Brain classification.jpg", "type": "image/jpeg", "size": 608058, "path": "Publication:haidacher_2010_statTF", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Brain classification.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Brain classification:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 597, 616, 161, 162, 166 ], "booktitle": "Proceedings of the IEEE Pacific Visualization 2010", "date_from": "2010-03-02", "date_to": "2010-03-05", "lecturer": [ 597 ], "pages_from": "17", "pages_to": "24", "research_areas": [], "keywords": [ "transfer function", "statistics", "shading", "noisy data", "classification" ], "weblinks": [], "files": [ { "description": "", "filetitle": "Brain classification", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1050, "image_height": 947, "name": "haidacher_2010_statTF-Brain classification.jpg", "type": "image/jpeg", "size": 608058, "path": "Publication:haidacher_2010_statTF", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Brain classification.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Brain classification:thumb{{size}}.png" }, { "description": "System in use", "filetitle": "Film clip", "main_file": false, "use_in_gallery": false, "access": "public", "preview_image_width": 1200, "preview_image_height": 800, "name": "haidacher_2010_statTF-Film clip.avi", "type": "video/x-msvideo", "size": 14340210, "path": "Publication:haidacher_2010_statTF", "preview_name": "haidacher_2010_statTF-Film clip:preview.png", "preview_type": "image/jpeg", "preview_size": 19755, "url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Film clip.avi", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Film clip:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Film clip:video.mp4" }, { "description": "", "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "haidacher_2010_statTF-Paper.pdf", "type": "application/pdf", "size": 3249151, "path": "Publication:haidacher_2010_statTF", "url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/haidacher_2010_statTF-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2010/haidacher_2010_statTF/", "__class": "Publication" }, { "id": "patel_2009_MC", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Moment Curves", "date": "2009-04", "abstract": "We define a transfer function based on the first and second statistical\r\nmoments. We consider the evolution of the mean and variance with\r\nrespect to a growing neighborhood around a voxel. This evolution\r\ndefines a curve in 3D for which we identify important trends and\r\nproject it back to 2D. The resulting 2D projection can be brushed\r\nfor easy and robust classification of materials and material borders.\r\nThe transfer function is applied to both CT and MR data.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "Moment Curves", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 916, "image_height": 858, "name": "patel_2009_MC-Moment Curves.jpg", "type": "image/jpeg", "size": 283414, "path": "Publication:patel_2009_MC", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/patel_2009_MC-Moment Curves.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/patel_2009_MC-Moment Curves:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 616, 597, 673, 166 ], "booktitle": "Proceedings of the IEEE Pacific Visualization Symposium 2009", "date_from": "2009-04-20", "date_to": "2009-04-23", "editor": "Peter Eades, Thomas Ertl, Han-Wei Shen", "isbn": "978-1-4244-4404-5", "lecturer": [ 616 ], "location": "Peking, China", "pages_from": "201", "pages_to": "208", "research_areas": [], "keywords": [ "Statistical Moments", "Volume Classification", "Statistics" ], "weblinks": [], "files": [ { "description": "", "filetitle": "Moment Curves", "main_file": true, "use_in_gallery": false, "access": "public", "image_width": 916, "image_height": 858, "name": "patel_2009_MC-Moment Curves.jpg", "type": "image/jpeg", "size": 283414, "path": "Publication:patel_2009_MC", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/patel_2009_MC-Moment Curves.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/patel_2009_MC-Moment Curves:thumb{{size}}.png" }, { "description": "", "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "patel_2009_MC-Paper.pdf", "type": "application/pdf", "size": 11779741, "path": "Publication:patel_2009_MC", "url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/patel_2009_MC-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/patel_2009_MC-Paper:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2009/patel_2009_MC/", "__class": "Publication" }, { "id": "haidacher-2008-vcbm", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Information-based Transfer Functions for Multimodal Visualization", "date": "2008-10", "abstract": "Transfer functions are an essential part of volume visualization. In multimodal visualization at least two values\r\nexist at every sample point. Additionally, other parameters, such as gradient magnitude, are often retrieved for\r\neach sample point. To find a good transfer function for this high number of parameters is challenging because of\r\nthe complexity of this task. In this paper we present a general information-based approach for transfer function\r\ndesign in multimodal visualization which is independent of the used modality types. Based on information theory,\r\nthe complex multi-dimensional transfer function space is fused to allow utilization of a well-known 2D transfer\r\nfunction with a single value and gradient magnitude as parameters. Additionally, a quantity is introduced which\r\nenables better separation of regions with complementary information. The benefit of the new method in contrast to\r\nother techniques is a transfer function space which is easy to understand and which provides a better separation\r\nof different tissues. The usability of the new approach is shown on examples of different modalities.", "authors_et_al": false, "substitute": null, "main_image": { "description": "Multimodal Visualization of CT and MRI", "filetitle": "CT-MRI", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1446, "image_height": 1446, "name": "haidacher-2008-vcbm-CT-MRI.jpg", "type": "image/jpeg", "size": 2466928, "path": "Publication:haidacher-2008-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-CT-MRI.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-CT-MRI:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 597, 161, 162, 166 ], "booktitle": "VCBM ", "editor": "C.P Botha, G. Kindlmann, W.J. Niessen, and B. Preim", "isbn": "978-3-905674-13-2", "issn": "2070-5778", "lecturer": [ 597 ], "location": "Delft", "pages_from": "101", "pages_to": "108", "publisher": "Eurographics Association", "research_areas": [], "keywords": [ "Multimodal Visualization", "Transfer Function", "Information Theory" ], "weblinks": [], "files": [ { "description": "Multimodal Visualization of CT and MRI", "filetitle": "CT-MRI", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1446, "image_height": 1446, "name": "haidacher-2008-vcbm-CT-MRI.jpg", "type": "image/jpeg", "size": 2466928, "path": "Publication:haidacher-2008-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-CT-MRI.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-CT-MRI:thumb{{size}}.png" }, { "description": "Multimodal Visualization of Neck Tumor", "filetitle": "CT-PET", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 1444, "image_height": 1167, "name": "haidacher-2008-vcbm-CT-PET.jpg", "type": "image/jpeg", "size": 1722886, "path": "Publication:haidacher-2008-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-CT-PET.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-CT-PET:thumb{{size}}.png" }, { "description": "Publication from VCBM 2008", "filetitle": "Paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "haidacher-2008-vcbm-Paper.pdf", "type": "application/pdf", "size": 11949177, "path": "Publication:haidacher-2008-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-Paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-Paper:thumb{{size}}.png" }, { "description": "Slides of Presentation at VCBM", "filetitle": "Presentation", "main_file": true, "use_in_gallery": false, "access": "public", "name": "haidacher-2008-vcbm-Presentation.pptx", "type": "application/x-zip", "size": 32101483, "path": "Publication:haidacher-2008-vcbm", "url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/haidacher-2008-vcbm-Presentation.pptx", "thumb_image_sizes": [] } ], "projects_workgroups": [ "diagvis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2008/haidacher-2008-vcbm/", "__class": "Publication" }, { "id": "haidacher-2007-idr", "type_id": "masterthesis", "tu_id": null, "repositum_id": null, "title": "Importance-Driven Rendering in Interventional Imaging", "date": "2007-08", "abstract": "In this thesis a combined visualization of dense clinical data like 3D CTA (Computed Tomography\r\nAngiography) combined with co-registered real-time images of medical intervention\r\napplications is presented. The main challenge here is to provide a merged visualization that\r\nallows su\u001ecient spatial perception of the important parts, as derived from the pre-operative\r\ndata, while not occluding the information in the real-time image embedded within the volume.\r\nThis work presents a new approach of importance de\u001cnition for volumetric data and how\r\nthis importance can be used to create a feature-emphasized visualization. Furthermore the\r\nviewpoint and the position of the intervention image is used to generate a contextual cutaway\r\nwhich in\u001duences the density of the visualization to avoid an occlusion of the real-time image\r\nby less important parts of the volumetric data.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "Result image (CTA)", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 506, "image_height": 448, "name": "haidacher-2007-idr-Result image (CTA).jpg", "type": "image/jpeg", "size": 95562, "path": "Publication:haidacher-2007-idr", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/haidacher-2007-idr-Result image (CTA).jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/haidacher-2007-idr-Result image (CTA):thumb{{size}}.png" }, "sync_repositum_override": null, 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(MRI).jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/haidacher-2007-idr-Result image (MRI):thumb{{size}}.png" }, { "description": "", "filetitle": "Video", "main_file": true, "use_in_gallery": false, "access": "public", "preview_image_width": 700, "preview_image_height": 526, "name": "haidacher-2007-idr-Video.avi", "type": "video/x-msvideo", "size": 7069324, "path": "Publication:haidacher-2007-idr", "preview_name": "haidacher-2007-idr-Video:preview.png", "preview_type": "image/jpeg", "preview_size": 41677, "url": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/haidacher-2007-idr-Video.avi", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/haidacher-2007-idr-Video:thumb{{size}}.png", "video_mp4": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/haidacher-2007-idr-Video:video.mp4" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2007/haidacher-2007-idr/", "__class": "Publication" }, { "id": "burns-2007-fea", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Feature Emphasis and Contextual Cutaways for Multimodal Medical Visualization", "date": "2007-05", "abstract": "Dense clinical data like 3D Computed Tomography (CT) scans can be visualized together with real-time imaging\nfor a number of medical intervention applications. However, it is difficult to provide a fused visualization that\nallows sufficient spatial perception of the anatomy of interest, as derived from the rich pre-operative scan, while\nnot occluding the real-time image displayed embedded within the volume.\nWe propose an importance-driven approach that presents the embedded data such that it is clearly visible along\nwith its spatial relation to the surrounding volumetric material. To support this, we present and integrate novel\ntechniques for importance specification, feature emphasis, and contextual cutaway generation.\nWe show results in a clinical context where a pre-operative CT scan is visualized alongside a tracked ultrasound\nimage, such that the important vasculature is depicted between the viewpoint and the ultrasound image, while a\nmore opaque representation of the anatomy is exposed in the surrounding area.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 325, "image_height": 308, "name": "burns-2007-fea-image.jpg", "type": "image/jpeg", "size": 39551, "path": "Publication:burns-2007-fea", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 676, 597, 677, 171, 166 ], "booktitle": "Proceedings of Eurographics / IEEE VGTC Symposium on Visualization (EuroVis 2007)", "date_from": "2007-05-23", "date_to": "2007-05-25", "editor": "K. 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Ynnerman", "isbn": "9783905673456", "lecturer": [ 676 ], "location": "Norköpping, Schweden", "pages_from": "275", "pages_to": "282", "publisher": "IEEE", "research_areas": [ "MedVis" ], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": false, "access": "public", "image_width": 325, "image_height": 308, "name": "burns-2007-fea-image.jpg", "type": "image/jpeg", "size": 39551, "path": "Publication:burns-2007-fea", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "burns-2007-fea-paper.pdf", "type": "application/pdf", "size": 11414491, "path": "Publication:burns-2007-fea", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-paper:thumb{{size}}.png" }, { "description": null, "filetitle": "presentation", "main_file": false, "use_in_gallery": false, "access": "public", "name": "burns-2007-fea-presentation.pdf", "type": "application/pdf", "size": 16305663, "path": "Publication:burns-2007-fea", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-presentation.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-presentation:thumb{{size}}.png" }, { "description": null, "filetitle": "videos", "main_file": false, "use_in_gallery": false, "access": "public", "name": "burns-2007-fea-videos.zip", "type": "application/zip", "size": 21424680, "path": "Publication:burns-2007-fea", "url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/burns-2007-fea-videos.zip", "thumb_image_sizes": [] } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2007/burns-2007-fea/", "__class": "Publication" }, { "id": "haidacher-2005-MND", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Multiscale Nodule Detection in CT Data", "date": "2005", "abstract": "In this paper I am describing a computer aided detection (CAD) method, which is able to detect lung nodules in medical data sets. The data sets are obtained by a high resolution computer tomography.\r\nThe goal of the nodule detection is to gain an early nodule detection which increases the probability of survival. Introduced method is able to detect nodules of variable size and variable shape. It is also rotation-invariant. The detection algorithm is based on the Hessian matrix. This matrix consists of the second-order partial derivatives. The eigenvalues of this matrix are used to determine the probability of\r\na nodule-like shape. This method is well adapted to detect nodules of a size larger than 4 mm diameter. Tests with synthetic nodule data sets and some real data sets provided a high probability of true nodule detection with a very low number of false positives per data set.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "picture", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 484, "image_height": 480, "name": "haidacher-2005-MND-picture.jpg", "type": "image/jpeg", "size": 71536, "path": "Publication:haidacher-2005-MND", "url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/haidacher-2005-MND-picture.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/haidacher-2005-MND-picture:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 597 ], "supervisor": [ 171 ], "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": "", "filetitle": "paper", "main_file": false, "use_in_gallery": false, "access": "public", "name": "haidacher-2005-MND-paper.pdf", "type": "application/pdf", "size": 741485, "path": "Publication:haidacher-2005-MND", "url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/haidacher-2005-MND-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/haidacher-2005-MND-paper:thumb{{size}}.png" }, { "description": "", "filetitle": "picture", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 484, "image_height": 480, "name": "haidacher-2005-MND-picture.jpg", "type": "image/jpeg", "size": 71536, "path": "Publication:haidacher-2005-MND", "url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/haidacher-2005-MND-picture.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/haidacher-2005-MND-picture:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2005/haidacher-2005-MND/", "__class": "Publication" }, { "id": "haidacher-2004-FVV", "type_id": "studentproject", "tu_id": null, "repositum_id": null, "title": "Merkmals-Visualisierung für Volumsdaten", "date": "2004", "abstract": "In diesem Paper werden Methoden vorgestellt, welche das Direct Volume Rendering (DVR) unterstutzen. Sie sollen vor allem dazu dienen, innere Strukturen und wichtige Details besser darzustellen. Die Methode Depth of Field adaptiert den Effekt der Tiefenunscharfe aus der Fotographie fur die Volumsvisualisierung. Der Fokusbereich wird dabei scharf dargestellt und je nach Entfernung in Blickrichtung vom Fokuspunkt und Linsenstarke, wird der jeweilige Bereich unscharfer dargestellt. Die Methode fuhrt dazu, dass der Benutzer schneller auf die wichtigen Teile des Datensatzes hingewiesen wird.\n\nDie weiteren Methoden beschaftigen sich mit der Darstellung der inneren Struktur von Objekten. Die Methode\ndes Focus+Context teilt dabei den Datensatz in einen Fokus und einen Kontextbereich. Objektteile, welche im Fokusbereich liegen, werden mittels DVR und den dazugehorigen Transferfunktionen gerendert. Der Rest\n wird mit einer nicht photorealistischen Methode gerendert, welche nur die Umrisse der Objekte darstellt. Bei 3D Dithering wird der Inhalt von gleichmaßig verteilten Wurfeln mit den vorgegebenen Transferfunktionen gerendert und vom dazwischen liegendem Rest werden nur die Konturen oder gar nichts dargestellt. Die\n letzte Methode, Magic Lamp, rendert Teile des Objektes mit DVR und den normalen Transferfunktionen nur\n dann, wenn deren Gradient nahezu parallel zu einer einstellbaren Richtung ist. Die restlichen Teile des\n Objekts werden wieder nur durch ihre Konturen dargestellt.\n\nhttp://www.cg.tuwien.ac.at/courses/projekte_old/vis/finished/MHaidacher/index.html", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 313, "image_height": 205, "name": "haidacher-2004-FVV-.jpg", "type": "image/jpeg", "size": 54397, "path": "Publication:haidacher-2004-FVV", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/haidacher-2004-FVV/haidacher-2004-FVV-.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/haidacher-2004-FVV/haidacher-2004-FVV-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 597 ], "supervisor": [ 171 ], "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "", 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