Vikram Apilla, B. Behrendt, K. Lawonn, B. Preim, M. Meuschke
{"title":"Automatic Animations to Analyze Blood Flow Data","authors":"Vikram Apilla, B. Behrendt, K. Lawonn, B. Preim, M. Meuschke","doi":"10.2312/vcbm.20211349","DOIUrl":null,"url":null,"abstract":"We present an approach for computing camera animations composed of optimal views to support the visual exploration of blood flow data using cerebral aneurysms as major example. Medical researchers are interested in hemodynamic parameters and vessel wall characteristics. The time-dependent character of blood flow data complicates the visual analysis. Our approach is modeled as an optimization problem to automatically determine camera paths during the cardiac cycle. These consist of optimal viewpoints showing regions with suspicious characteristics of walland flow-related parameters. This provides medical researchers with an efficient method of obtaining a fast overview of patient-specific blood flow data. CCS Concepts • Applied computing → Life and medical sciences; • Human-centered computing → Visualization;","PeriodicalId":88872,"journal":{"name":"Eurographics Workshop on Visual Computing for Biomedicine","volume":"1 1","pages":"101-105"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurographics Workshop on Visual Computing for Biomedicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/vcbm.20211349","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We present an approach for computing camera animations composed of optimal views to support the visual exploration of blood flow data using cerebral aneurysms as major example. Medical researchers are interested in hemodynamic parameters and vessel wall characteristics. The time-dependent character of blood flow data complicates the visual analysis. Our approach is modeled as an optimization problem to automatically determine camera paths during the cardiac cycle. These consist of optimal viewpoints showing regions with suspicious characteristics of walland flow-related parameters. This provides medical researchers with an efficient method of obtaining a fast overview of patient-specific blood flow data. CCS Concepts • Applied computing → Life and medical sciences; • Human-centered computing → Visualization;