{"title":"Segmentation of anti-nuclear antibody images based on the watershed approach","authors":"Chung-Chuan Cheng, J. Taur, T. Hsieh, C. Tao","doi":"10.1109/ICIEA.2010.5515233","DOIUrl":null,"url":null,"abstract":"Fluorescence patterns at present are usually examined laboriously by experienced physicians through manually inspecting the slides with the help of a microscope. The readings in indirect immunofluorescene (IIF) usually suffer from the disadvantages such as the inter-observer variability that limits the reproducibility. This study proposes a segmented method based on the watershed algorithm to detect the edges of HEp-2 cells automatically. Experimental results show that the system has an overall correct rate of 92.81%. This system can be used as a preprocessing system for an automatic HEp-2 cells identification system.","PeriodicalId":234296,"journal":{"name":"2010 5th IEEE Conference on Industrial Electronics and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 5th IEEE Conference on Industrial Electronics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA.2010.5515233","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Fluorescence patterns at present are usually examined laboriously by experienced physicians through manually inspecting the slides with the help of a microscope. The readings in indirect immunofluorescene (IIF) usually suffer from the disadvantages such as the inter-observer variability that limits the reproducibility. This study proposes a segmented method based on the watershed algorithm to detect the edges of HEp-2 cells automatically. Experimental results show that the system has an overall correct rate of 92.81%. This system can be used as a preprocessing system for an automatic HEp-2 cells identification system.