Pavel A. Govyadinov, Tasha R Womack, J. Eriksen, D. Mayerich, Guoning Chen
{"title":"微血管网络的图形辅助可视化","authors":"Pavel A. Govyadinov, Tasha R Womack, J. Eriksen, D. Mayerich, Guoning Chen","doi":"10.1109/VISUAL.2019.8933682","DOIUrl":null,"url":null,"abstract":"Microvessels are frequent targets for research into tissue development and disease progression. These complex and subtle differences between networks are currently difficult to visualize, making sample comparisons subjective and difficult to quantify. These challenges are due to the structure of microvascular networks, which are sparse but space-filling. This results in a complex and interconnected mesh that is difficult to represent and impractical to interpret using conventional visualization techniques. We develop a bi-modal visualization framework, leveraging graph-based and geometry-based techniques to achieve interactive visualization of microvascular networks. This framework allows researchers to objectively interpret the complex and subtle variations that arise when comparing microvascular networks.","PeriodicalId":192801,"journal":{"name":"2019 IEEE Visualization Conference (VIS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Graph-Assisted Visualization of Microvascular Networks\",\"authors\":\"Pavel A. Govyadinov, Tasha R Womack, J. Eriksen, D. Mayerich, Guoning Chen\",\"doi\":\"10.1109/VISUAL.2019.8933682\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Microvessels are frequent targets for research into tissue development and disease progression. These complex and subtle differences between networks are currently difficult to visualize, making sample comparisons subjective and difficult to quantify. These challenges are due to the structure of microvascular networks, which are sparse but space-filling. This results in a complex and interconnected mesh that is difficult to represent and impractical to interpret using conventional visualization techniques. We develop a bi-modal visualization framework, leveraging graph-based and geometry-based techniques to achieve interactive visualization of microvascular networks. This framework allows researchers to objectively interpret the complex and subtle variations that arise when comparing microvascular networks.\",\"PeriodicalId\":192801,\"journal\":{\"name\":\"2019 IEEE Visualization Conference (VIS)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Visualization Conference (VIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VISUAL.2019.8933682\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Visualization Conference (VIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VISUAL.2019.8933682","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Graph-Assisted Visualization of Microvascular Networks
Microvessels are frequent targets for research into tissue development and disease progression. These complex and subtle differences between networks are currently difficult to visualize, making sample comparisons subjective and difficult to quantify. These challenges are due to the structure of microvascular networks, which are sparse but space-filling. This results in a complex and interconnected mesh that is difficult to represent and impractical to interpret using conventional visualization techniques. We develop a bi-modal visualization framework, leveraging graph-based and geometry-based techniques to achieve interactive visualization of microvascular networks. This framework allows researchers to objectively interpret the complex and subtle variations that arise when comparing microvascular networks.