{"title":"三维非线性不可见边界检测滤波器","authors":"M. Petrou, F. Mohanna, V. Kovalev","doi":"10.1109/TDPVT.2004.1335421","DOIUrl":null,"url":null,"abstract":"The human vision system can discriminate regions which differ up to the second order statistics only. A lot of malignant tumours have boundaries which are not visible to the human eye. We present an algorithm designed to reveal \"hidden\" boundaries in grey level images, by computing gradients in higher order statistics of the data. We demonstrate it by applying it to the identification of possible \"hidden\" boundaries of gliomas as manifest themselves in MRI 3D scans.","PeriodicalId":191172,"journal":{"name":"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"3D non-linear invisible boundary detection filters\",\"authors\":\"M. Petrou, F. Mohanna, V. Kovalev\",\"doi\":\"10.1109/TDPVT.2004.1335421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The human vision system can discriminate regions which differ up to the second order statistics only. A lot of malignant tumours have boundaries which are not visible to the human eye. We present an algorithm designed to reveal \\\"hidden\\\" boundaries in grey level images, by computing gradients in higher order statistics of the data. We demonstrate it by applying it to the identification of possible \\\"hidden\\\" boundaries of gliomas as manifest themselves in MRI 3D scans.\",\"PeriodicalId\":191172,\"journal\":{\"name\":\"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TDPVT.2004.1335421\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDPVT.2004.1335421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
3D non-linear invisible boundary detection filters
The human vision system can discriminate regions which differ up to the second order statistics only. A lot of malignant tumours have boundaries which are not visible to the human eye. We present an algorithm designed to reveal "hidden" boundaries in grey level images, by computing gradients in higher order statistics of the data. We demonstrate it by applying it to the identification of possible "hidden" boundaries of gliomas as manifest themselves in MRI 3D scans.