{"title":"用于有效数据库标记的眼动追踪:结肠镜检查视频自动分析的应用","authors":"F. Vilariño, G. Lacey","doi":"10.1109/IMVIP.2007.18","DOIUrl":null,"url":null,"abstract":"In this paper we present our preliminary results in the automatic analysis of colonoscopy video using eye-tracking. We propose that eye-tracking can be successfully applied to solve different problems in computer assisted colonoscopy, such as database labelling, expertise assessment and abnormality detection. We provide results in these three areas, including a machine learning-based system for colon cancer detection using data generated with eye-tracking.","PeriodicalId":249544,"journal":{"name":"International Machine Vision and Image Processing Conference (IMVIP 2007)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Eye-tracking for efficient database labelling: Applications to automatic analysis of colonoscopy video\",\"authors\":\"F. Vilariño, G. Lacey\",\"doi\":\"10.1109/IMVIP.2007.18\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present our preliminary results in the automatic analysis of colonoscopy video using eye-tracking. We propose that eye-tracking can be successfully applied to solve different problems in computer assisted colonoscopy, such as database labelling, expertise assessment and abnormality detection. We provide results in these three areas, including a machine learning-based system for colon cancer detection using data generated with eye-tracking.\",\"PeriodicalId\":249544,\"journal\":{\"name\":\"International Machine Vision and Image Processing Conference (IMVIP 2007)\",\"volume\":\"66 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Machine Vision and Image Processing Conference (IMVIP 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMVIP.2007.18\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Machine Vision and Image Processing Conference (IMVIP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMVIP.2007.18","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Eye-tracking for efficient database labelling: Applications to automatic analysis of colonoscopy video
In this paper we present our preliminary results in the automatic analysis of colonoscopy video using eye-tracking. We propose that eye-tracking can be successfully applied to solve different problems in computer assisted colonoscopy, such as database labelling, expertise assessment and abnormality detection. We provide results in these three areas, including a machine learning-based system for colon cancer detection using data generated with eye-tracking.
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