[ { "id": "Cruz-thesis", "type_id": "phdthesis", "tu_id": null, "repositum_id": null, "title": "3D Modelling and Reconstruction of Peripheral Vascular Structure", "date": "2006-03", "abstract": "A model is a simplified representation of an object. The modeling stage could be described as shaping individual objects that are later used in the scene. For many years scientists are trying to create an appropriate model of the blood vessels. It looks quite intuitive to believe that a blood vessel can be modeled as a tubular object, and this is true, but the problems appear when you want to create an accurate model that can deal with the wide variability of shapes of diseased blood vessels. From the medical point of view it is quite important to identify, not just the center of the vessel lumen but also the center of the vessel, particularly in the presences of some anomalies, which is the case diseased blood vessels.\r\n\r\nAn accurate estimation of vessel parameters is a prerequisite for automated visualization and analysis of healthy and diseased blood vessels. We believe that a model-based technique is the most suitable one for parameterizing blood vessels. The main focus of this work is to present a new strategy to parameterize diseased blood vessels of the lower extremity arteries.\r\n\r\nThe first part presents an evaluation of different methods for approximating the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray casting using thresholds and a maximum gradient-like stop criterion, pixel-motion estimation between successive images called block matching, center of gravity and shape based segmentation. The Randomized Hough Transform and ellipse fitting have been used as shape based segmentation techniques. Since in the synthetic data set the centerline is known, an estimation of the error can be calculated in order to determine the accuracy achieved by a given method.\r\n\r\nThe second part describes an estimation of the dimensions of lower extremity arteries, imaged by computed tomography. The vessel is modeled using an elliptical or cylindrical structure with specific dimensions, orientation and CT attenuation values. The model separates two homogeneous regions: Its inner side represents a region of density for vessels, and its outer side a region for background. Taking into account the point spread function of a CT scanner, which is modeled using a Gaussian kernel, in order to smooth the vessel boundary in the model. An optimization process is used to find the best model that fits with the data input. The method provides center location, diameter and orientation of the vessel as well as blood and background mean density values.\r\n\r\nThe third part presents the result of a clinical evaluation of our methods, as a prerequisite step for being used in clinical environment. To perform this evaluation, twenty cases from available patient data were selected and classified as 'mildly diseased' and 'severely diseased' datasets. Manual identification was used as our reference standard. We compared the model fitting method against a standard method, which is currently used in the clinical environment. In general, the mean distance error for every method was within the inter-operator variability. However, the non-linear model fitting technique based on a cylindrical model shows always a better center approximation in most of the cases, 'mildly diseased' as well as 'severely diseased' cases. Clinically, the non-linear model fitting technique is more robust and presented a better estimation in most of the cases. Nevertheless, the radiologists and clinical experts have the last word with respect to the use of this technique in clinical environment.", "authors_et_al": false, "substitute": null, "main_image": { "description": "", "filetitle": "pdf", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Cruz-thesis-pdf.pdf", "type": "application/pdf", "size": 7916402, "path": "Publication:Cruz-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2006/Cruz-thesis/Cruz-thesis-pdf.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2006/Cruz-thesis/Cruz-thesis-pdf:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168 ], "date_end": "2006-03", "date_start": "2002-05", "supervisor": [ 166 ], "research_areas": [], "keywords": [ "Vessel Visualization", "3D Modeling", "Segmentation", "3D Reconstruction" ], "weblinks": [], "files": [ { "description": "", "filetitle": "pdf", "main_file": true, "use_in_gallery": true, "access": "public", "name": "Cruz-thesis-pdf.pdf", "type": "application/pdf", "size": 7916402, "path": "Publication:Cruz-thesis", "url": "https://www.cg.tuwien.ac.at/research/publications/2006/Cruz-thesis/Cruz-thesis-pdf.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2006/Cruz-thesis/Cruz-thesis-pdf:thumb{{size}}.png" } ], "projects_workgroups": [ "AngioVis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2006/Cruz-thesis/", "__class": "Publication" }, { "id": "LaCruz2004", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Non-linear Model Fitting to Parameterize Diseased Blood Vessels", "date": "2004-10", "abstract": "Accurate estimation of vessel parameters is a prerequisite for automated visualization and analysis of normal and diseased blood vessels. The objective of this research is to estimate the dimensions of lower extremity arteries, imaged by computed tomography (CT). The vessel is modeled using an elliptical or cylindrical structure with specific dimensions, orientation and blood vessel mean density. The model separates two homogeneous regions: Its inner side represents a region of density for vessels, and its outer side a region for background. Taking into account the point spread function (PSF) of a CT scanner, a function is modeled with a Gaussian kernel, in order to smooth the vessel boundary in the model. A new strategy for vessel parameter estimation is presented. It stems from vessel model and model parameter optimization by a nonlinear optimization procedure (the Levenberg-Marquardt technique). The method provides center location, diameter and orientation of the vessel as well as blood and background mean density values. The method is tested on synthetic data and real patient data with encouraging results.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 600, "image_height": 600, "name": "LaCruz2004-image.jpg", "type": "image/jpeg", "size": 30878, "path": "Publication:LaCruz2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/LaCruz2004-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/LaCruz2004-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168, 167, 169, 170, 166, 164 ], "booktitle": "IEEE Visualization 2004", "editor": "IEEE", "isbn": "0-7803-8788-0", "location": "Austin, Texas", "organization": "Institute of Computer Graphics and Algorithms, Vienna University of Technology", "pages_from": "400", "pages_to": "393", "publisher": "IEEE", "research_areas": [], "keywords": [ "Visualiyation", "Segmentation", "Blood Vessel Detection" ], "weblinks": [], "files": [ { "description": null, "filetitle": "alacruzVIS2004", "main_file": true, "use_in_gallery": false, "access": "public", "name": "LaCruz2004-alacruzVIS2004.pdf", "type": "application/pdf", "size": 1806922, "path": "Publication:LaCruz2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/LaCruz2004-alacruzVIS2004.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/LaCruz2004-alacruzVIS2004:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 600, "image_height": 600, "name": "LaCruz2004-image.jpg", "type": "image/jpeg", "size": 30878, "path": "Publication:LaCruz2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/LaCruz2004-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/LaCruz2004-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz2004/", "__class": "Publication" }, { "id": "StrakaVis2004", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "The VesselGlyph: Focus & Context Visualization in CT-Angiography", "date": "2004-10", "abstract": "Reliable and complete blood-vessel segmentation is still a challenging problem. This is especially true in the presence of morphologic changes resulting from atherosclerotic diseases. In this paper we take advantage of partially segmented data with approximately identified vessel centerlines to comprehensively visualize the diseased peripheral arterial tree. We introduce the VesselGlyph as an abstract notation for novel focus & context visualization techniques of tubular structures such as contrast-medium enhanced arteries in CT-Angiography (CT-A). The proposed techniques combine direct volume rendering (DVR) and curved planar reformation (CPR) within a single image. The VesselGlyph consists of several regions where different rendering methods are used. Region type, the used visualization method and region parameters depend on the distance from the vessel centerline and on viewing parameters as well. By selecting proper rendering techniques for different regions, vessels are depicted in a naturally looking and undistorted anatomic context. In this paper we furthermore present a way how to implement the proposed techniques in software and by means of modern 3D graphics accelerators.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 618, "image_height": 750, "name": "StrakaVis2004-image.jpg", "type": "image/jpeg", "size": 91043, "path": "Publication:StrakaVis2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/StrakaVis2004-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/StrakaVis2004-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 347, 168, 169, 170, 166, 164 ], "booktitle": "IEEE Visualization 2004", "editor": "IEEE", "location": "Austin, Texas", "organization": "Commision for Scientific Visualization, Austrian", "pages_from": "392", "pages_to": "385", "publisher": "IEEE", "research_areas": [], "keywords": [ "focus & Context Technique", "Direct Volume Rendering", "Curved Planar Reformation", "Vessel Visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "StrakaVis2004-.pdf", "type": "application/pdf", "size": 1060701, "path": "Publication:StrakaVis2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/StrakaVis2004-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/StrakaVis2004-:thumb{{size}}.png" }, { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 618, "image_height": 750, "name": "StrakaVis2004-image.jpg", "type": "image/jpeg", "size": 91043, "path": "Publication:StrakaVis2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/StrakaVis2004-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/StrakaVis2004-image:thumb{{size}}.png" } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/StrakaVis2004/", "__class": "Publication" }, { "id": "alacruzVisSym2004", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Accuracy Evaluation of Diferent Centerline Approximations of Blood Vessels", "date": "2004-05", "abstract": " Accurate determination of the central vessel axis is a prerequisite for automated arteries diseases visualization and quantification. In this paper we present an evaluation of different methods used to approximate the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray casting technique using thresholds and maximum gradient-like stop criterion, pixel motion estimation between successive images called block matching, center of gravity and shape based segmentation. The Randomized Hough Transform and ellipse fitting using Lagrange Multiplier have been used as shape based segmentation techniques, fitting an elliptical shape to a set of points. The synthetic data simulate the peripheral arterial tree (aorta-to-pedal). The vessel diameter changes along the z-axis from about 0.7 to about 23 voxels. The data dimension is 256x256x768 with voxel size 0.5x0.5x0.5mm. In this data set the centerline is known and an estimation of the error is calculated in order to determine how precise a given method is and to classify it accordingly.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "alacruzVisSym2004-.pdf", "type": "application/pdf", "size": 1484850, "path": "Publication:alacruzVisSym2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/alacruzVisSym2004/alacruzVisSym2004-.pdf", "thumb_image_sizes": [] }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168 ], "booktitle": "Symposium on Visualization 2004", "editor": "EUROGRAPHICS / IEEE TCGV", "location": "Konstanz, Germany", "organization": "Institute of Computer Graphics and Algorithms, Vienna University of Technology", "pages_from": "120", "pages_to": "115", "publisher": "IEEE", "research_areas": [], "keywords": [ "Center Line Detection", "Vessel Segmentation", "Medical Visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "alacruzVisSym2004-.pdf", "type": "application/pdf", "size": 1484850, "path": "Publication:alacruzVisSym2004", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/alacruzVisSym2004/alacruzVisSym2004-.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/alacruzVisSym2004/", "__class": "Publication" }, { "id": "LaCruz-2004-NMF", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Non-linear Model Fitting to Parameterize Diseased Blood Vessels", "date": "2004-04", "abstract": "Accurate estimation of vessel parameters is a prerequisite for automated visualization and analysis of normal and diseased blood vessels. The objective of this research is to estimate the dimensions of lower extremity arteries, imaged by computed tomography (CT).\nThe vessel is modeled using an elliptical or cylindrical structure with specific dimensions, orientation and blood vessel mean density. The model separates two homogeneous regions: Its inner side represents a region of density for vessels, and its outer side a region for background. Taking into account the point spread function (PSF) of a CT scanner, a function is modeled with a Gaussian kernel, in order to smooth the vessel boundary in the model. A new strategy for vessel parameter estimation is presented. It\nstems from vessel model and model parameter optimization by a nonlinear optimization procedure (the Levenberg-Marquardt technique). The method provides center location, diameter and orientation of the vessel as well as blood and background mean density values. The method is tested on synthetic data and real patient data with encouraging results.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168, 167, 169, 170, 166, 164 ], "number": "TR-186-2-04-05", "pages_from": "1", "pages_to": "8", "research_areas": [], "keywords": [ "Diseased Blood Vessel Detection", "Segmentation", "Visualization" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "LaCruz-2004-NMF-paper.pdf", "type": "application/pdf", "size": 3123971, "path": "Publication:LaCruz-2004-NMF", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz-2004-NMF/LaCruz-2004-NMF-paper.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/LaCruz-2004-NMF/", "__class": "Publication" }, { "id": "Straka-2004-TVG", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "The VesselGlyph: Focus & Context Visualization in CT-Angiography", "date": "2004-04", "abstract": "Reliable and complete blood-vessel segmentation is still a challenging problem. This is especially true in the presence of morphologic changes resulting from atherosclerotic diseases. In this paper we take advantage of partially segmented data with approximately identified vessel centerlines to comprehensively visualize the diseased peripheral arterial tree.\r\nWe introduce the VesselGlyph as an abstract notation for novel focus & context visualization techniques of tubular structures such as contrast-medium enhanced arteries in CT-Angiography (CT-A). The proposed techniques combine direct volume rendering (DVR) and curved planar reformation (CPR) within a single image. The VesselGlyph consists of several regions where different rendering methods are used. Region type, the used visualization method and region parameters depend on the distance from the vessel centerline and on viewing parameters as well. By selecting proper rendering techniques for different regions, vessels are depicted in a naturally looking and undistorted anatomic context.\r\nIn this paper we furthermore present a way how to implement the proposed techniques in software and by means of modern 3D graphics accelerators.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 618, "image_height": 750, "name": "Straka-2004-TVG-image.jpg", "type": "image/jpeg", "size": 91043, "path": "Publication:Straka-2004-TVG", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/Straka-2004-TVG-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/Straka-2004-TVG-image:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 347, 168, 169, 170, 166, 164 ], "number": "TR-186-2-04-04", "pages_from": "1", "pages_to": "8", "research_areas": [], "keywords": [ "vessel visualization.", "focus & context technique", "curved planar reformation", "direct volume rendering" ], "weblinks": [], "files": [ { "description": null, "filetitle": "image", "main_file": false, "use_in_gallery": true, "access": "public", "image_width": 618, "image_height": 750, "name": "Straka-2004-TVG-image.jpg", "type": "image/jpeg", "size": 91043, "path": "Publication:Straka-2004-TVG", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/Straka-2004-TVG-image.jpg", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/Straka-2004-TVG-image:thumb{{size}}.png" }, { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2004-TVG-paper.pdf", "type": "application/pdf", "size": 5201440, "path": "Publication:Straka-2004-TVG", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/Straka-2004-TVG-paper.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/Straka-2004-TVG-paper:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-TVG/", "__class": "Publication" }, { "id": "alacruzECR2004", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Accuracy of Automated Centerline Approximation Algorithms for Lower Extremity Vessels in CTA Phantom", "date": "2004-03", "abstract": "Purpose: The accurate determination of the central vessel axis is a prerequisite for automated visualization (curved planar reformation) and quantitation. The purpose of this work was to assess the accuracy of different algorithms for automated centerline detection in a phantom simulating the peripheral arterial tree.\r\nMethods and Material: Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel (aorto-to-pedal arteries, diameter 18-0.6mm) dataset (256x256x600, voxel size 0.5x0.5x0.5mm). They are ray-casting/thresholding (RCT), ray-casting/maximum gradient (RCMG), block matching (BM), fitting to ellipse (FE), center of gravity (CoG), and Randomized Hough transform (RHT). Gaussian noise whith a sigma: 0, 5 and 10 was used to observe the accuracy of the method under noise influence The accuracy of automatic centerline determination was quantified by measuring the error-distance between the derived centerlines, and the known centerline course of the synthetic dataset.\r\nResults: BM demonstrated unacceptable performance in large vessels (>5mm) when the shift used was less than 3 voxels. RCMG demonstrated a greater error (mean of the error 4.73mm) in large diameter (>15mm) vessels than in small diameter (<15mm) vessels (mean of the error 0.64mm). Because RHT and FE use Canny edge detector preprocessing, both are sensitive to noise. CoG and RCT keep the mean of the error-distance significantly smaller (0.7mm and 0.9mm respectively) than all other algorithms.\r\nConclusion: CoG and RCT algorithms provide the most efficient centerline approximation over a wide range of vessel diameters. ", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168, 167, 169, 170, 166, 164 ], "booktitle": "European Congres of Radiology", "location": "Vienna, Austria", "organization": "Institute of Computer Graphics and Algorithms, Vienna University of Technology", "research_areas": [], "keywords": [ "Medical Visualization", "Vessel Segmentation", "Centerline Detection" ], "weblinks": [], "files": [], "projects_workgroups": [ "vis" ], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/alacruzECR2004/", "__class": "Publication" }, { "id": "Straka-2004-BSA", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Bone Segmentation in CT-Angiography Data Using a Probabilistic Atlas", "date": "2004-01", "abstract": "Automatic segmentation of bony structures in CT angiography datasets is an essential pre-processing step necessary for most visualization and analysis tasks. Since traditional density and gradient operators fail in non-trivial cases (or at least require extensive operator work), we propose a new method for segmentation of CTA data based on a probabilistic atlas. Storing densities and marks of previously manually segmented tissues to the atlas can constitute a statistical information base for latter accurate segmentation. In order to eliminate dimensional and anatomic variability of the atlas input datasets, these have to be spatially normalized (registered) first by applying a non-rigid transformation. After this transformation, densities and tissue masks are statistically processed (e.g averaged) within the atlas. Records in the atlas can be later evaluated for estimating the probability of bone tissue in a voxel of an unsegmented dataset.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 168, 236, 170, 164, 166 ], "number": "TR-186-2-04-01", "pages_from": "1", "pages_to": "8", "research_areas": [], "keywords": [ "Histogram Classification", "Distance Fields", "Thin-Plate Spline", "Probabilistic Atlas", "Knowledge Based Segmentation", "CT Angiography" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2004-BSA-paper.pdf", "type": "application/pdf", "size": 747482, "path": "Publication:Straka-2004-BSA", "url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-BSA/Straka-2004-BSA-paper.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2004/Straka-2004-BSA/", "__class": "Publication" }, { "id": "La Cruz-2003-AEC", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Accuracy Evaluation of Different Centerline Approximations of Blood Vessels", "date": "2003-11", "abstract": "Accurate determination of the central vessel axis is a prerequisite for automated arteries diseases visualization and quantification. In this paper we present an evaluation of different methods used to approximate the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray casting technique using thresholds and maximum gradient-like stop criterion, pixel motion estimation between successive images called block matching, center of gravity and shape based segmentation. The Randomized Hough Transform and ellipse fitting using Lagrange Multiplier have been used as shape based segmentation techniques, fitting an elliptical shape to a set of points. The synthetic data simulate the peripheral arterial tree (aorta-to-pedal). The vessel diameter changes along the z-axis from about 0.7 to about 23 voxels. The data dimension is 256x256x768 with voxel size 0.5x0.5x0.5mm. In this data set the centerline is known and an estimation of the error is calculated in order to determine how precise a given method is and to classify it accordingly.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168 ], "number": "TR-186-2-03-12", "pages_from": "1", "pages_to": "TR-186-2-03-13Paper.pdf", "research_areas": [], "keywords": [ "Medical Visualization", "Vessel Segmentation", "Centerline Detection" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "La Cruz-2003-AEC-paper.pdf", "type": "application/pdf", "size": 1706086, "path": "Publication:La Cruz-2003-AEC", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/La Cruz-2003-AEC/La Cruz-2003-AEC-paper.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/La Cruz-2003-AEC/", "__class": "Publication" }, { "id": "La Cruz-2003-AECX", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "Accuracy Evaluation of Different Centerline Approximations of Blood Vessels", "date": "2003-11", "abstract": "Accurate determination of the central vessel axis is a prerequisite for automated arteries diseases visualization and quantification. In this paper we present an evaluation of different methods used to approximate the centerline of the vessel in a phantom simulating the peripheral arteries. Six algorithms were used to determine the centerline of a synthetic peripheral arterial vessel. They are based on: ray casting technique using thresholds and maximum gradient-like stop criterion, pixel motion estimation between successive images called block matching, center of gravity and shape based segmentation. The Randomized Hough Transform and ellipse fitting using Lagrange Multiplier have been used as shape based segmentation techniques, fitting an elliptical shape to a set of points. The synthetic data simulate the peripheral arterial tree (aorta-to-pedal). The vessel diameter changes along the z-axis from about 0.7 to about 23 voxels. The data dimension is 256x256x768 with voxel size 0.5x0.5x0.5mm. In this data set the centerline is known and an estimation of the error is calculated in order to determine how precise a given method is and to classify it accordingly.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 168 ], "number": "TR-186-2-03-12", "pages_from": "1", "pages_to": "11", "research_areas": [], "keywords": [ "Medical Visualization", "Vessel Segmentation", "Centerline Detection" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "La Cruz-2003-AECX-paper.pdf", "type": "application/pdf", "size": 1706086, "path": "Publication:La Cruz-2003-AECX", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/La Cruz-2003-AECX/La Cruz-2003-AECX-paper.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/La Cruz-2003-AECX/", "__class": "Publication" }, { "id": "Straka-2003-Bon", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "Bone Segmentation in CT-Angiography Data Using a Probabilistic Atlas", "date": "2003-11", "abstract": "Automatic segmentation of bony structures in CT angiography datasets is an essential pre-processing step necessary for most visualization and analysis tasks. Since traditional density and gradient operators fail in non-trivial cases (or at last require extensive operator work), we propose a new method for segmentation of CTA data based on a probabilistic atlas. Sorting densities and masks of previously manually segmented tissues to the atlas can constitute a statistical information base for latter accurate segmentation. In order to eliminate dimensional and anatomic variability of the atlas input datasets, these have to be spatially normalized (registered) first by applying a non-rigid transformation. After this transformation, densities and tissue masks are statistically processed (e.g. averaged) within the atlas. Records in the atlas can be later evaluated for estimating the probability of bone tissue in a voxel of an unsegmented dataset.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2003-Bon-.pdf", "type": "application/pdf", "size": 747482, "path": "Publication:Straka-2003-Bon", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Bon/Straka-2003-Bon-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Bon/Straka-2003-Bon-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 168, 236, 170, 164, 166 ], "booktitle": "Vision, Modeling and Visualization", "pages_from": "505", "pages_to": "512", "publisher": "VMV", "research_areas": [], "keywords": [ "Knowledge Based Segmentation", "CT Angiography", "Probabilistic Atlas", "Thin-Plate Spline", "Distance Fields", "Histogram Classficication" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2003-Bon-.pdf", "type": "application/pdf", "size": 747482, "path": "Publication:Straka-2003-Bon", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Bon/Straka-2003-Bon-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Bon/Straka-2003-Bon-:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Bon/", "__class": "Publication" }, { "id": "Straka-2003-CTA", "type_id": "techreport", "tu_id": null, "repositum_id": null, "title": "3D Watershed Transform Combined with a Probabilistic Atlas for Medical Image Segmentation", "date": "2003-11", "abstract": "Recent advances in medical imaging technology using multiple detector-row computed tomography (CT) provide volumetric datasets with unprecedented spatial resolution. This has allowed for CT to evolve into an excellent non-invasive vascular imaging technology, commonly referred to as CT-angiography. Visualization of vascular structures from CT datasets is demanding, however, and identification of anatomic objects in CT-datasets is highly desirable. Density and/or gradient operators have been used most commonly to classify CT data. In CT angiography, simple density/gradient operators do not allow precise and reliable classification of tissues due to the fact that different tissues (e.g. bones and vessels) possess the same density range and may lie in close spatial vicinity. We hypothesize, that anatomic classification can be achieved more accurately, if both spatial location and density properties of volume data are taken into account. We present a combination of two well-known methods for volume data processing to obtain accurate tissue classification. 3D watershed transform is used to partition the volume data in morphologically consistent blocks and a probabilistic anatomic atlas is used to distinguish between different kinds of tissues based on their density.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 168, 169, 170, 164, 166 ], "number": "TR-186-2-03-13", "pages_from": "1", "pages_to": "8", "research_areas": [], "keywords": [ "Histogram Classification", "Thin-Plate-Spline", "Probabilistic Atlas", "Knowledge Based Segmentation", "CT Angiography" ], "weblinks": [], "files": [ { "description": null, "filetitle": "paper", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2003-CTA-paper.pdf", "type": "application/pdf", "size": 656919, "path": "Publication:Straka-2003-CTA", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-CTA/Straka-2003-CTA-paper.pdf", "thumb_image_sizes": [] } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-CTA/", "__class": "Publication" }, { "id": "Buehler-2003-Geo", "type_id": "inbook", "tu_id": null, "repositum_id": null, "title": "Geometric Methods for Vessel Visualization and Quantification- A Survey", "date": "2003", "abstract": "Visualization and quantitative analysis of vessel data is an important preprocessing step in diagnosis of vascular diseases, monitoring, surgery planning, blood flow simulation, education and training surgeons. This paper surveys several geometric methods to solve basic visualization and quantification problems like centerline computation, boundary detection, projections techniques, and geometric model generation.", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 231, 189, 168 ], "booktitle": "Geometric Modelling for Scientific Visualization", "editor": "G. Brunnett, B. Hamann, H. Müller", "isbn": "ISBN: 3-540-40116-4", "pages": "?", "pages_from": "421", "pages_to": "399", "publisher": "Springer", "research_areas": [], "keywords": [], "weblinks": [], "files": [], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Buehler-2003-Geo/", "__class": "Publication" }, { "id": "Straka-2003-3DW", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "3D Watershed Transform Combined with a Probabilistic Atlas for Medical Image Segmentation", "date": "2003", "abstract": " Recent advances in medical imaging technology using multiple detector-row computed tomography (CT) provide volumetric datasets with unprecedented spatial resolution. This has allowed for CT to evolve into an excellent non-invasive vascular imaging technology, commonly referred to as CT-angiography. Visualization of vascular structures from CT datasets is demanding, however, and identification of anatomic objects in CT-datasets is highly desirable. Density and/or gradient operators have been used most commonly to classify CT data. In CT angiography, simple density/gradient operators do not allow precise and reliable classification of tissues due to the fact that different tissues (e.g. bones and vessels) possess the same density range and may lie in close spatial vicinity. We hypothesize, that anatomic classification can be achieved more accurately, if both spatial location and density properties of volume data are taken into account. We present a combination of two well-known methods for volume data processing to obtain accurate tissue classification. 3D watershed transform is used to partition the volume data in morphologically consistent blocks and a probabilistic anatomic atlas is used to distinguish between different kinds of tissues based on their density.", "authors_et_al": false, "substitute": null, "main_image": { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2003-3DW-.pdf", "type": "application/pdf", "size": 1481982, "path": "Publication:Straka-2003-3DW", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-3DW/Straka-2003-3DW-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-3DW/Straka-2003-3DW-:thumb{{size}}.png" }, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 168, 169, 170, 166, 164 ], "booktitle": "MIT 2003", "journal": "Journal of Medical Informatics & Technologies", "research_areas": [], "keywords": [ "Thin-Plate-Spline", "Knowledge Based Segmentation Probabilist", "CT Angiography", "Histogram Classification" ], "weblinks": [], "files": [ { "description": null, "filetitle": "", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2003-3DW-.pdf", "type": "application/pdf", "size": 1481982, "path": "Publication:Straka-2003-3DW", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-3DW/Straka-2003-3DW-.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-3DW/Straka-2003-3DW-:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-3DW/", "__class": "Publication" }, { "id": "Straka-2003-Apr", "type_id": "inproceedings", "tu_id": null, "repositum_id": null, "title": "A probabilistic atlas of the lower extremity arterial tree for perpheral CT angiography", "date": "2003", "abstract": "", "authors_et_al": false, "substitute": null, "main_image": null, "sync_repositum_override": null, "repositum_presentation_id": null, "authors": [ 167, 170, 168, 169, 166, 164 ], "booktitle": "European Congress of Radiology", "publisher": "ECR", "research_areas": [], "keywords": [], "weblinks": [], "files": [ { "description": null, "filetitle": "PDF", "main_file": true, "use_in_gallery": false, "access": "public", "name": "Straka-2003-Apr-PDF.pdf", "type": "application/pdf", "size": 10487, "path": "Publication:Straka-2003-Apr", "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Apr/Straka-2003-Apr-PDF.pdf", "thumb_image_sizes": [ 16, 64, 100, 175, 300, 600 ], "thumb_url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Apr/Straka-2003-Apr-PDF:thumb{{size}}.png" } ], "projects_workgroups": [], "url": "https://www.cg.tuwien.ac.at/research/publications/2003/Straka-2003-Apr/", "__class": "Publication" } ]