基于纹理的HE染色组织图像分割算法改进

2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI) Pub Date : 2013-11-01 DOI:10.1109/CINTI.2013.6705205

G. Windisch, M. Kozlovszky

{"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}

引用次数: 5

摘要

超像素算法正成为许多计算机视觉应用中广泛使用的一种方法，它可以作为HE染色组织样本的数字显微镜图像分割的基础。研究结果表明，在众多的超像素方法中，SLIC在正常图像的边界附着精度方面取得了最好的效果。为了找出它是否可以用于分割组织图像，我们设计了一个基准来衡量SLIC的性能，并尝试通过仔细调整参数来提高性能，使SLIC更好地适应我们的特殊图像处理需求。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2013 IEEE 14th International Symposium on Computational Intelligence and Informatics (CINTI)

自引率

0.00%

发文量