The colon is an organ whose constant motility poses difficulties to its analysis. Although morphological data can be successfully extracted from Computational Tomography, its radiative nature makes it only indicated for patients with disorders. Only recently, acquisition techniques that rely on the use of Magnetic Resonance Imaging have matured enough to enable the generation of morphological colon data of healthy patients without preparation (i. e. administration of drugs or contrast agents). As a result, a database of colon morphological data for patients under different diets, has been created. Currently, the digestologists we collaborate with analyze the measured data of the gut by inspecting a set of spreadsheets. In this paper, we propose a system for the exploratory visual analysis of the whole database of morphological data at once. It provides features for the visual comparison of data correlations, the inspection of the morphological measures, as well 3D rendering of the colon segmented models. The system solely relies on the use of web technologies, which makes it portable even to mobile devices.
{"title":"A Web-based Application for the Visual Exploration of Colon Morphology Data","authors":"J. Males, E. Monclús, José Díaz, Pere-Pau Vázquez","doi":"10.2312/VCBM.20191228","DOIUrl":"https://doi.org/10.2312/VCBM.20191228","url":null,"abstract":"The colon is an organ whose constant motility poses difficulties to its analysis. Although morphological data can be successfully extracted from Computational Tomography, its radiative nature makes it only indicated for patients with disorders. Only recently, acquisition techniques that rely on the use of Magnetic Resonance Imaging have matured enough to enable the generation of morphological colon data of healthy patients without preparation (i. e. administration of drugs or contrast agents). As a result, a database of colon morphological data for patients under different diets, has been created. Currently, the digestologists we collaborate with analyze the measured data of the gut by inspecting a set of spreadsheets. In this paper, we propose a system for the exploratory visual analysis of the whole database of morphological data at once. It provides features for the visual comparison of data correlations, the inspection of the morphological measures, as well 3D rendering of the colon segmented models. The system solely relies on the use of web technologies, which makes it portable even to mobile devices.","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"101 1","pages":"27-31"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73232425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christoph Haarburger, N. Horst, D. Truhn, Mirjam Broeckmann, S. Schrading, C. Kuhl, D. Merhof
Generative adversarial networks have been shown to alleviate the problem of limited training data for supervised learning problems in medical image computing. However, most generative models for medical images focus on image-to-image translation rather than de novo image synthesis. In many clinical applications, image acquisition is multiparametric, i.e. includes contrast-enchanced or diffusion-weighted imaging. We present a generative adversarial network that synthesizes a sequence of temporally consistent contrast-enhanced breast MR image patches. Performance is evaluated quantitatively using the Fréchet Inception Distance, achieving a minimum FID of 21.03. Moreover, a qualitative human reader test shows that even a radiologist cannot differentiate between real and fake images easily. CCS Concepts • Computing methodologies → Modeling methodologies;
{"title":"Multiparametric Magnetic Resonance Image Synthesis using Generative Adversarial Networks","authors":"Christoph Haarburger, N. Horst, D. Truhn, Mirjam Broeckmann, S. Schrading, C. Kuhl, D. Merhof","doi":"10.2312/VCBM.20191226","DOIUrl":"https://doi.org/10.2312/VCBM.20191226","url":null,"abstract":"Generative adversarial networks have been shown to alleviate the problem of limited training data for supervised learning problems in medical image computing. However, most generative models for medical images focus on image-to-image translation rather than de novo image synthesis. In many clinical applications, image acquisition is multiparametric, i.e. includes contrast-enchanced or diffusion-weighted imaging. We present a generative adversarial network that synthesizes a sequence of temporally consistent contrast-enhanced breast MR image patches. Performance is evaluated quantitatively using the Fréchet Inception Distance, achieving a minimum FID of 21.03. Moreover, a qualitative human reader test shows that even a radiologist cannot differentiate between real and fake images easily. CCS Concepts • Computing methodologies → Modeling methodologies;","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"1 1","pages":"11-15"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82974734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, radar technology has increasingly been used for the monitoring of bird migration. Marine radars are often utilized for this purpose because of their wide accessibility, range, and resolution. They allow the tracking of birds even at night—when most bird migration takes place—over extended periods of time. This creates a wealth of radar images, for which manual annotation of bird tracks is not feasible. We propose a tool for automatic bird tracking and visualization from marine radar imagery. For this purpose, we developed a bird tracking algorithm for vertically recorded radar images that is able to extract quantitative parameters including flight direction, height, and duration. The results can be qualitatively verified by a visualization design that enables domain experts the time-dependent visualization of bird tracks. Furthermore, it allows a preprocessing of radar images taken by screen capturing for device independence. Our tool was used in an ornithological monitoring study to analyze over 200.000 vertically recorded radar images taken in multiple observation periods and locations.
{"title":"Feasibility Study For Automatic Bird Tracking and Visualization from Time-Dependent Marine Radar Imagery","authors":"F. Ganglberger, K. Bühler","doi":"10.2312/vcbm.20191231","DOIUrl":"https://doi.org/10.2312/vcbm.20191231","url":null,"abstract":"In recent years, radar technology has increasingly been used for the monitoring of bird migration. Marine radars are often utilized for this purpose because of their wide accessibility, range, and resolution. They allow the tracking of birds even at night—when most bird migration takes place—over extended periods of time. This creates a wealth of radar images, for which manual annotation of bird tracks is not feasible. We propose a tool for automatic bird tracking and visualization from marine radar imagery. For this purpose, we developed a bird tracking algorithm for vertically recorded radar images that is able to extract quantitative parameters including flight direction, height, and duration. The results can be qualitatively verified by a visualization design that enables domain experts the time-dependent visualization of bird tracks. Furthermore, it allows a preprocessing of radar images taken by screen capturing for device independence. Our tool was used in an ornithological monitoring study to analyze over 200.000 vertically recorded radar images taken in multiple observation periods and locations.","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"192 1","pages":"51-55"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89009942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Corvó, M. A. Westenberg, R. Wimberger-Friedl, Stephan Fromme, Michel A. Peeters, M. A. Driel, J. V. Wijk
The advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite of clear future improvements in the diagnostic workflow, questions on how to effectively support the pathologists and how to integrate current data sources and quantitative information still persist. In this context, Visual Analytics (VA) - as the discipline that aids users to solve complex problems with an interactive and visual approach - can play a vital role to support the cognitive skills of pathologists and the large volumes of data available. To identify the main opportunities to employ VA in digital pathology systems, we conducted a survey with 20 pathologists to characterize the diagnostic practice and needs from a user perspective. From our findings, we discuss how VA can leverage quantitative image data to empower pathologists with new advanced digital pathology systems.
{"title":"Visual Analytics in Digital Pathology: Challenges and Opportunities","authors":"A. Corvó, M. A. Westenberg, R. Wimberger-Friedl, Stephan Fromme, Michel A. Peeters, M. A. Driel, J. V. Wijk","doi":"10.2312/VCBM.20191240","DOIUrl":"https://doi.org/10.2312/VCBM.20191240","url":null,"abstract":"The advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite of clear future improvements in the diagnostic workflow, questions on how to effectively support the pathologists and how to integrate current data sources and quantitative information still persist. In this context, Visual Analytics (VA) - as the discipline that aids users to solve complex problems with an interactive and visual approach - can play a vital role to support the cognitive skills of pathologists and the large volumes of data available. To identify the main opportunities to employ VA in digital pathology systems, we conducted a survey with 20 pathologists to characterize the diagnostic practice and needs from a user perspective. From our findings, we discuss how VA can leverage quantitative image data to empower pathologists with new advanced digital pathology systems.","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"1 1","pages":"129-143"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90785184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniela Modena, D. Bassano, A. Elevelt, M. Baragona, P. Hilbers, M. A. Westenberg
High Intensity Focused Ultrasound (HIFU) is a non invasive therapeutic method, which has been a subject of interest for the treatment of various kinds of tumors. Despite the numerous advantages, HIFU techniques do not reach the high delivery precision like other therapies (e.g., radiotherapy). For this reason, a correct therapy planning and monitoring in HIFU treatments remains a challenge. We propose HIFUpm, a visual analytics approach which enables the visualization of the HIFU simulation results, while guiding the user in the evaluation of the procedure. We illustrate the use of HIFUpm for an ablative treatment of an osteoid osteoma. This use case demonstrates that HIFUpm provides a flexible visual environment to plan and monitor HIFU procedures.
{"title":"HIFUpm: a Visual Environment to Plan and Monitor High Intensity Focused Ultrasound Treatments","authors":"Daniela Modena, D. Bassano, A. Elevelt, M. Baragona, P. Hilbers, M. A. Westenberg","doi":"10.2312/vcbm.20191246","DOIUrl":"https://doi.org/10.2312/vcbm.20191246","url":null,"abstract":"High Intensity Focused Ultrasound (HIFU) is a non invasive therapeutic method, which has been a subject of interest for the treatment of various kinds of tumors. Despite the numerous advantages, HIFU techniques do not reach the high delivery precision like other therapies (e.g., radiotherapy). For this reason, a correct therapy planning and monitoring in HIFU treatments remains a challenge. We propose HIFUpm, a visual analytics approach which enables the visualization of the HIFU simulation results, while guiding the user in the evaluation of the procedure. We illustrate the use of HIFUpm for an ablative treatment of an osteoid osteoma. This use case demonstrates that HIFUpm provides a flexible visual environment to plan and monitor HIFU procedures.","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"14 1","pages":"207-211"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91107752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tobias Rau, Sebastian Zahn, M. Krone, G. Reina, T. Ertl
Depictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule’s potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that has the potential to exceed the memory limitations of current hardware. Here we show that rendering using CPU ray tracing also reaches interactive frame rates without hard limitations to memory. In our results large molecule complexes can be rendered with only the precomputation of each individual SES, and no further involved representation or transformation. Additionally, we provide advanced visualization techniques like ambient occlusion opacity mapping (AOOM) to enhance the comprehensibility of the molecular structure. CPU ray tracing not only provides very high image quality and global illumination, which is beneficial for the perception of spatial structures, it also opens up the possibility to visualize larger data sets and to render on any HPC cluster. Our results demonstrate that simple instancing of geometry keeps the memory consumption for rendering large molecule complexes low, so the examination of much larger data is also possible. (see https://www.acm.org/publications/class-2012) CCS Concepts •Human-centered computing → Scientific visualization; • Computing methodologies → Ray tracing; • Applied computing → Molecular structural biology;
{"title":"Interactive CPU-based Ray Tracing of Solvent Excluded Surfaces","authors":"Tobias Rau, Sebastian Zahn, M. Krone, G. Reina, T. Ertl","doi":"10.2312/vcbm.20191249","DOIUrl":"https://doi.org/10.2312/vcbm.20191249","url":null,"abstract":"Depictions of molecular surfaces such as the Solvent Excluded Surface (SES) can provide crucial insight into functional molecular properties, such as the molecule’s potential to react. The interactive visualization of single and multiple molecule surfaces is essential for the data analysis by domain experts. Nowadays, the SES can be rendered at high frame rates using shader-based ray casting on the GPU. However, rendering large molecules or larger molecule complexes requires large amounts of memory that has the potential to exceed the memory limitations of current hardware. Here we show that rendering using CPU ray tracing also reaches interactive frame rates without hard limitations to memory. In our results large molecule complexes can be rendered with only the precomputation of each individual SES, and no further involved representation or transformation. Additionally, we provide advanced visualization techniques like ambient occlusion opacity mapping (AOOM) to enhance the comprehensibility of the molecular structure. CPU ray tracing not only provides very high image quality and global illumination, which is beneficial for the perception of spatial structures, it also opens up the possibility to visualize larger data sets and to render on any HPC cluster. Our results demonstrate that simple instancing of geometry keeps the memory consumption for rendering large molecule complexes low, so the examination of much larger data is also possible. (see https://www.acm.org/publications/class-2012) CCS Concepts •Human-centered computing → Scientific visualization; • Computing methodologies → Ray tracing; • Applied computing → Molecular structural biology;","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"66 1","pages":"239-251"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90673281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Amin Abbasloo, Vitalis Wiens, T. Schmidt-Wilcke, P. Sundgren, R. Klein, T. Schultz
When Diffusion Tensor Imaging (DTI) is used in clinical studies, statistical hypothesis testing is the standard approach to establish significant differences between groups, such as patients and healthy controls. However, diffusion tensors contain six degrees of freedom, and the most commonly used univariate tests reduce them to a single scalar, such as Fractional Anisotropy. Multivariate tests that account for the full tensor information have been developed, but have not been widely adopted in practice. Based on analyzing the limitations of existing univariate and multivariate tests, we argue that it is beneficial to use a more flexible, steerable test. Therefore, we introduce a test that can be customized to include any subset of tensor attributes that are relevant to the analysis task at hand. We also present a visual analytics system that supports the exploratory task of customizing it to a specific scenario. Our system closely integrates quantitative analysis with suitable visualizations. It links spatial and abstract views to reveal clusters of strong differences, to relate them to the affected anatomical structures, and to visually compare the results of different tests. A use case is presented in which our system leads to the formation of several new hypotheses about the effects of systemic lupus erythematosus on water diffusion in the brain. (Less)
{"title":"Interactive Formation of Statistical Hypotheses in Diffusion Tensor Imaging","authors":"Amin Abbasloo, Vitalis Wiens, T. Schmidt-Wilcke, P. Sundgren, R. Klein, T. Schultz","doi":"10.2312/vcbm.20191229","DOIUrl":"https://doi.org/10.2312/vcbm.20191229","url":null,"abstract":"When Diffusion Tensor Imaging (DTI) is used in clinical studies, statistical hypothesis testing is the standard approach to establish significant differences between groups, such as patients and healthy controls. However, diffusion tensors contain six degrees of freedom, and the most commonly used univariate tests reduce them to a single scalar, such as Fractional Anisotropy. Multivariate tests that account for the full tensor information have been developed, but have not been widely adopted in practice. Based on analyzing the limitations of existing univariate and multivariate tests, we argue that it is beneficial to use a more flexible, steerable test. Therefore, we introduce a test that can be customized to include any subset of tensor attributes that are relevant to the analysis task at hand. We also present a visual analytics system that supports the exploratory task of customizing it to a specific scenario. Our system closely integrates quantitative analysis with suitable visualizations. It links spatial and abstract views to reveal clusters of strong differences, to relate them to the affected anatomical structures, and to visually compare the results of different tests. A use case is presented in which our system leads to the formation of several new hypotheses about the effects of systemic lupus erythematosus on water diffusion in the brain. (Less)","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"33 1","pages":"33-43"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80706079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the Molecular Dynamics (MD) visualization literature, different approaches are utilized to study protein-lipid interactions (PLI) and protein-protein interaction (PPI) in decoupled contexts. However, the two types of interaction occur in the same space-time domain. It is beneficial to study the PLI and PPI in a unified context. Nevertheless, the simulation’s size, length, and complexity increase the challenge of understanding the dynamic behavior. We propose a novel framework consisting of four linked views, a time-dependent 3D view, a novel hybrid view, a clustering timeline, and a details-on-demand window. We introduce a selection of visual designs to convey the behavior of PLI and PPI through a unified coordinate system. Abstraction is used to present proteins in hybrid 2D space, a projected tiled space is used to present both PLI and PPI at the particle level in a heat-map style visual design while glyphs are used to represent PPI at the molecular level. We couple visually separable visual designs in a unified coordinate space. The result lets the user study both PLI and PPI separately or together in a unified visual analysis framework. We also exemplify its use with case studies focusing on protein clustering and we report domain expert
{"title":"Hybrid Visualization of Protein-Lipid and Protein-Protein Interaction","authors":"Naif Alharbi, M. Krone, M. Chavent, R. Laramee","doi":"10.2312/vcbm.20191247","DOIUrl":"https://doi.org/10.2312/vcbm.20191247","url":null,"abstract":"In the Molecular Dynamics (MD) visualization literature, different approaches are utilized to study protein-lipid interactions (PLI) and protein-protein interaction (PPI) in decoupled contexts. However, the two types of interaction occur in the same space-time domain. It is beneficial to study the PLI and PPI in a unified context. Nevertheless, the simulation’s size, length, and complexity increase the challenge of understanding the dynamic behavior. We propose a novel framework consisting of four linked views, a time-dependent 3D view, a novel hybrid view, a clustering timeline, and a details-on-demand window. We introduce a selection of visual designs to convey the behavior of PLI and PPI through a unified coordinate system. Abstraction is used to present proteins in hybrid 2D space, a projected tiled space is used to present both PLI and PPI at the particle level in a heat-map style visual design while glyphs are used to represent PPI at the molecular level. We couple visually separable visual designs in a unified coordinate space. The result lets the user study both PLI and PPI separately or together in a unified visual analysis framework. We also exemplify its use with case studies focusing on protein clustering and we report domain expert","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"10 1","pages":"213-223"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73428170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Furmanová, B. Kozlíková, Vojtěch Vonásek, J. Byška
{"title":"DockVis: Visual Analysis of Molecular Docking Data","authors":"K. Furmanová, B. Kozlíková, Vojtěch Vonásek, J. Byška","doi":"10.2312/vcbm.20191238","DOIUrl":"https://doi.org/10.2312/vcbm.20191238","url":null,"abstract":"","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"6 1","pages":"113-122"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88805506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Walczak, J. Georgii, L. Tautz, M. Neugebauer, I. Wamala, S. Sündermann, V. Falk, A. Hennemuth
In mitral valve interventions, surgeons have to select an optimal combination of techniques for every patient. Especially less experienced physicians would benefit from decision support for this process. To support the visual analysis of the patientspecific valvular dynamics and an in-silico pre-intervention simulation of different therapy options, a real-time simulation of the mitral valve is needed, especially for the use in a time-constrained clinical environment. We develop a simplified model of the mitral valve and propose a novel approach to simulate the mitral valve with position-based dynamics. As input, a mesh representation of the open-state mitral valve, two polygons representing the open and closed annulus states, simplified chordae tendineae, and a set of forces for approximating the surrounding blood are required. The mitral valve model can be deformed to simulate the closing and opening as well as incorporate changes caused by virtual interventions in the simulation. For evaluation, ten mitral valves were reconstructed from transesophageal echocardiogram sequences of patients with normal and abnormal physiology. Experts in cardiac surgery annotated anatomical landmarks for valve reconstruction. The simulation results for closing the valve were qualitatively compared to the anatomy depicted in the image sequences and, if present, the reproduction of a prolapse was verified. In addition, two virtual interventions (annuloplasty and clipping) were performed for one case and provided new insights about changes in valve closure and orifice area after modification. Each simulation ran at interactive frame rates. Our approach enables an efficient simulation of the mitral valve with normal and abnormal valve closing behavior as well as virtual interventions. The simulation results showed good agreements with the image data in general and reproduced valve closure in all cases. In three cases, prolapse was not or not correctly reproduced. Further research is needed to parameterize the model in pathologic cases. CCS Concepts • Applied computing → Life and medical sciences; Health informatics;
{"title":"Using Position-Based Dynamics for Simulating the Mitral Valve in a Decision Support System","authors":"L. Walczak, J. Georgii, L. Tautz, M. Neugebauer, I. Wamala, S. Sündermann, V. Falk, A. Hennemuth","doi":"10.2312/vcbm.20191242","DOIUrl":"https://doi.org/10.2312/vcbm.20191242","url":null,"abstract":"In mitral valve interventions, surgeons have to select an optimal combination of techniques for every patient. Especially less experienced physicians would benefit from decision support for this process. To support the visual analysis of the patientspecific valvular dynamics and an in-silico pre-intervention simulation of different therapy options, a real-time simulation of the mitral valve is needed, especially for the use in a time-constrained clinical environment. We develop a simplified model of the mitral valve and propose a novel approach to simulate the mitral valve with position-based dynamics. As input, a mesh representation of the open-state mitral valve, two polygons representing the open and closed annulus states, simplified chordae tendineae, and a set of forces for approximating the surrounding blood are required. The mitral valve model can be deformed to simulate the closing and opening as well as incorporate changes caused by virtual interventions in the simulation. For evaluation, ten mitral valves were reconstructed from transesophageal echocardiogram sequences of patients with normal and abnormal physiology. Experts in cardiac surgery annotated anatomical landmarks for valve reconstruction. The simulation results for closing the valve were qualitatively compared to the anatomy depicted in the image sequences and, if present, the reproduction of a prolapse was verified. In addition, two virtual interventions (annuloplasty and clipping) were performed for one case and provided new insights about changes in valve closure and orifice area after modification. Each simulation ran at interactive frame rates. Our approach enables an efficient simulation of the mitral valve with normal and abnormal valve closing behavior as well as virtual interventions. The simulation results showed good agreements with the image data in general and reproduced valve closure in all cases. In three cases, prolapse was not or not correctly reproduced. Further research is needed to parameterize the model in pathologic cases. CCS Concepts • Applied computing → Life and medical sciences; Health informatics;","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"7 1","pages":"165-175"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78967483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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