{"title":"利用邻域图减少算法对乳腺图像进行病灶分割","authors":"Seyyedeh Marziyeh Hamedi, H. E. Komleh","doi":"10.1109/KBEI.2015.7436162","DOIUrl":null,"url":null,"abstract":"Classification of soft tissues is often joined with uncertainty and ultimate areas border might be hardly measured in segmentation. Basic techniques of edge detection can be used to determine the boundary edge, but because of noise and gray levels steep changes in medical images, it is difficult to achieve the edge of a lesion in image with reasonable and precise segmentation. In this paper a graph based algorithm is presented to extract alike region in image, this approach helps finding similar lesions and accurate segmentation.","PeriodicalId":168295,"journal":{"name":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Segmentation of breast images to find the lesions using the decreased neighborhood graph algorithm\",\"authors\":\"Seyyedeh Marziyeh Hamedi, H. E. Komleh\",\"doi\":\"10.1109/KBEI.2015.7436162\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Classification of soft tissues is often joined with uncertainty and ultimate areas border might be hardly measured in segmentation. Basic techniques of edge detection can be used to determine the boundary edge, but because of noise and gray levels steep changes in medical images, it is difficult to achieve the edge of a lesion in image with reasonable and precise segmentation. In this paper a graph based algorithm is presented to extract alike region in image, this approach helps finding similar lesions and accurate segmentation.\",\"PeriodicalId\":168295,\"journal\":{\"name\":\"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/KBEI.2015.7436162\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KBEI.2015.7436162","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation of breast images to find the lesions using the decreased neighborhood graph algorithm
Classification of soft tissues is often joined with uncertainty and ultimate areas border might be hardly measured in segmentation. Basic techniques of edge detection can be used to determine the boundary edge, but because of noise and gray levels steep changes in medical images, it is difficult to achieve the edge of a lesion in image with reasonable and precise segmentation. In this paper a graph based algorithm is presented to extract alike region in image, this approach helps finding similar lesions and accurate segmentation.