M. Ismail, S. Elhabian, A. Farag, G. Dryden, A. Seow
{"title":"3D自动结肠分割有效的息肉检测","authors":"M. Ismail, S. Elhabian, A. Farag, G. Dryden, A. Seow","doi":"10.1109/CIBEC.2012.6473334","DOIUrl":null,"url":null,"abstract":"With polyps being the main cause of colorectal cancer, accurate colon segmentation is a crucial step for polyp detection in a virtual colonoscopy system. This paper presents a fully automated segmentation framework for the colon which is based on convex formulation of the active contour model. Our approach is tested on 7 sets where the results are further validated for polyp detection. Results show the efficiency of the framework with an overall accuracy of 99%, and high sensitivity of polyp detection.","PeriodicalId":416740,"journal":{"name":"2012 Cairo International Biomedical Engineering Conference (CIBEC)","volume":"306 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"3D automated colon segmentation for efficient polyp detection\",\"authors\":\"M. Ismail, S. Elhabian, A. Farag, G. Dryden, A. Seow\",\"doi\":\"10.1109/CIBEC.2012.6473334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With polyps being the main cause of colorectal cancer, accurate colon segmentation is a crucial step for polyp detection in a virtual colonoscopy system. This paper presents a fully automated segmentation framework for the colon which is based on convex formulation of the active contour model. Our approach is tested on 7 sets where the results are further validated for polyp detection. Results show the efficiency of the framework with an overall accuracy of 99%, and high sensitivity of polyp detection.\",\"PeriodicalId\":416740,\"journal\":{\"name\":\"2012 Cairo International Biomedical Engineering Conference (CIBEC)\",\"volume\":\"306 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Cairo International Biomedical Engineering Conference (CIBEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIBEC.2012.6473334\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Cairo International Biomedical Engineering Conference (CIBEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIBEC.2012.6473334","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
3D automated colon segmentation for efficient polyp detection
With polyps being the main cause of colorectal cancer, accurate colon segmentation is a crucial step for polyp detection in a virtual colonoscopy system. This paper presents a fully automated segmentation framework for the colon which is based on convex formulation of the active contour model. Our approach is tested on 7 sets where the results are further validated for polyp detection. Results show the efficiency of the framework with an overall accuracy of 99%, and high sensitivity of polyp detection.