{"title":"利用广义正态分布优化全切片图像分割","authors":"K.P. Shivamurthy, Dr. Raju.A. S","doi":"10.47392/irjaeh.2024.0185","DOIUrl":null,"url":null,"abstract":"Whole slide image (WSI) segmentation is a crucial task aiding tumour and cancerous cell diagnosis. Generalized Normal Distribution Optimization (GNDO) algorithm is adopted for whole slide image segmentation based on thresholding in this paper. GNDO algorithm utilizes the generalized normal distribution's properties to determine the ideal thresholds for image segmentation. Through various metrics, the efficacy of GNDO in comparison to traditional Otsu thresholding methods is demonstrated. As demonstrated by the results, it can offer reliable and flexible solutions for different histopathology images.","PeriodicalId":517766,"journal":{"name":"International Research Journal on Advanced Engineering Hub (IRJAEH)","volume":"16 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Whole Slide Image Segmentation Using Generalized Normal Distribution Optimization\",\"authors\":\"K.P. Shivamurthy, Dr. Raju.A. S\",\"doi\":\"10.47392/irjaeh.2024.0185\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Whole slide image (WSI) segmentation is a crucial task aiding tumour and cancerous cell diagnosis. Generalized Normal Distribution Optimization (GNDO) algorithm is adopted for whole slide image segmentation based on thresholding in this paper. GNDO algorithm utilizes the generalized normal distribution's properties to determine the ideal thresholds for image segmentation. Through various metrics, the efficacy of GNDO in comparison to traditional Otsu thresholding methods is demonstrated. As demonstrated by the results, it can offer reliable and flexible solutions for different histopathology images.\",\"PeriodicalId\":517766,\"journal\":{\"name\":\"International Research Journal on Advanced Engineering Hub (IRJAEH)\",\"volume\":\"16 9\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Research Journal on Advanced Engineering Hub (IRJAEH)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.47392/irjaeh.2024.0185\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Research Journal on Advanced Engineering Hub (IRJAEH)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47392/irjaeh.2024.0185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal Whole Slide Image Segmentation Using Generalized Normal Distribution Optimization
Whole slide image (WSI) segmentation is a crucial task aiding tumour and cancerous cell diagnosis. Generalized Normal Distribution Optimization (GNDO) algorithm is adopted for whole slide image segmentation based on thresholding in this paper. GNDO algorithm utilizes the generalized normal distribution's properties to determine the ideal thresholds for image segmentation. Through various metrics, the efficacy of GNDO in comparison to traditional Otsu thresholding methods is demonstrated. As demonstrated by the results, it can offer reliable and flexible solutions for different histopathology images.