{"title":"使用关联物理和特征空间视图的多场医疗数据的交互式可视化","authors":"Jorik Blaas, C. Botha, F. Post","doi":"10.2312/VisSym/EuroVis07/123-130","DOIUrl":null,"url":null,"abstract":"Multi-field datasets contain multiple parameters defined over the same spatio-temporal domain. In medicine, such multi-field data is being used more often every day, and there is an urgent need for exploratory visualization approaches that are able to deal effectively with the data-analysis. In this paper, we present a highly interactive, coordinated view-based visualization approach that has been developed especially for dealing with multi-field medical data. It can show any number of views of the physical domain and also of the abstract high-dimensional feature space. The approach has been optimized for interactive use with very large datasets. It is based on intuitive interaction techniques, and integrates analysis techniques from pattern classification to guide the exploration process. We will give some details about the implementation, and we demonstrate the utility of our approach with two real medical use cases.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"51","resultStr":"{\"title\":\"Interactive Visualization of Multi-Field Medical Data Using Linked Physical and Feature-Space Views\",\"authors\":\"Jorik Blaas, C. Botha, F. Post\",\"doi\":\"10.2312/VisSym/EuroVis07/123-130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multi-field datasets contain multiple parameters defined over the same spatio-temporal domain. In medicine, such multi-field data is being used more often every day, and there is an urgent need for exploratory visualization approaches that are able to deal effectively with the data-analysis. In this paper, we present a highly interactive, coordinated view-based visualization approach that has been developed especially for dealing with multi-field medical data. It can show any number of views of the physical domain and also of the abstract high-dimensional feature space. The approach has been optimized for interactive use with very large datasets. It is based on intuitive interaction techniques, and integrates analysis techniques from pattern classification to guide the exploration process. We will give some details about the implementation, and we demonstrate the utility of our approach with two real medical use cases.\",\"PeriodicalId\":224719,\"journal\":{\"name\":\"Eurographics Conference on Visualization\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"51\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Eurographics Conference on Visualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2312/VisSym/EuroVis07/123-130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Eurographics Conference on Visualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2312/VisSym/EuroVis07/123-130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Interactive Visualization of Multi-Field Medical Data Using Linked Physical and Feature-Space Views
Multi-field datasets contain multiple parameters defined over the same spatio-temporal domain. In medicine, such multi-field data is being used more often every day, and there is an urgent need for exploratory visualization approaches that are able to deal effectively with the data-analysis. In this paper, we present a highly interactive, coordinated view-based visualization approach that has been developed especially for dealing with multi-field medical data. It can show any number of views of the physical domain and also of the abstract high-dimensional feature space. The approach has been optimized for interactive use with very large datasets. It is based on intuitive interaction techniques, and integrates analysis techniques from pattern classification to guide the exploration process. We will give some details about the implementation, and we demonstrate the utility of our approach with two real medical use cases.