{"title":"基于纹理的HE染色组织图像分割算法改进","authors":"G. Windisch, M. Kozlovszky","doi":"10.1109/CINTI.2013.6705205","DOIUrl":null,"url":null,"abstract":"Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.","PeriodicalId":439949,"journal":{"name":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Improvement of texture based image segmentation algorithm for HE stained tissue samples\",\"authors\":\"G. Windisch, M. Kozlovszky\",\"doi\":\"10.1109/CINTI.2013.6705205\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.\",\"PeriodicalId\":439949,\"journal\":{\"name\":\"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CINTI.2013.6705205\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CINTI.2013.6705205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improvement of texture based image segmentation algorithm for HE stained tissue samples
Superpixel algorithms are becoming a widely used method for many computer vision applications, and it could be used as a basis of image segmentation for digital microscopy images of HE stained tissue samples. Research results show that among the many superpixel methods SLIC yields the best results when it comes to boundary adherence accuracy for normal images. In an effort to find out if it can be used for segmenting tissue images we have devised a benchmark to measure the performance of SLIC and tried improving the performance by careful tuning of the parameters to better fit SLIC to our special image processing needs.