{"title":"A Windows Mobile Based Application for Detection of Cancer in Squamous Cell","authors":"Y. Karunakar, A. Kuwadekar, K. Narayanan","doi":"10.1109/NGMAST.2010.16","DOIUrl":null,"url":null,"abstract":"Pathological labs use manual method for detection of cancer cells recognition and techniques which are languorous for cell counting. This paper presents automatic cancer cell detection for squamous epithelia in window based applications in mobile phones and PDAs. The algorithm preprocesses the images to remove the graininess, enhance the contrast between the cytoplasm and nucleus and extra cellular components. After preprocessing steps Fourier transform analysis [4, 5] is done to organize the images. Averaging is done to reduce the noise in Fourier image and a 1-D line plot is done so that the cancerous tissue can be differentiated by the machine. Subsequently, the segmentation algorithm based on Otsu’s threshold, morphological operations, and cell size considerations is performed. Biologists can now prepare and image thousands of samples per day using this automation.","PeriodicalId":184193,"journal":{"name":"2010 Fourth International Conference on Next Generation Mobile Applications, Services and Technologies","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Fourth International Conference on Next Generation Mobile Applications, Services and Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NGMAST.2010.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Pathological labs use manual method for detection of cancer cells recognition and techniques which are languorous for cell counting. This paper presents automatic cancer cell detection for squamous epithelia in window based applications in mobile phones and PDAs. The algorithm preprocesses the images to remove the graininess, enhance the contrast between the cytoplasm and nucleus and extra cellular components. After preprocessing steps Fourier transform analysis [4, 5] is done to organize the images. Averaging is done to reduce the noise in Fourier image and a 1-D line plot is done so that the cancerous tissue can be differentiated by the machine. Subsequently, the segmentation algorithm based on Otsu’s threshold, morphological operations, and cell size considerations is performed. Biologists can now prepare and image thousands of samples per day using this automation.
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