{"id":988,"date":"2023-11-01T17:29:13","date_gmt":"2023-11-01T17:29:13","guid":{"rendered":"http:\/\/digital-health.one\/roundtable\/2023\/?page_id=988"},"modified":"2023-11-03T09:38:24","modified_gmt":"2023-11-03T09:38:24","slug":"krishna-gopal-dhal","status":"publish","type":"page","link":"http:\/\/digital-health.one\/roundtable\/2023\/krishna-gopal-dhal\/","title":{"rendered":"Krishna Gopal Dhal"},"content":{"rendered":"<div id=\"pl-gb988-69f0505aded16\"  class=\"panel-layout\" ><div id=\"pg-gb988-69f0505aded16-0\"  class=\"panel-grid panel-no-style\" ><div id=\"pgc-gb988-69f0505aded16-0-0\"  class=\"panel-grid-cell\" ><div id=\"panel-gb988-69f0505aded16-0-0-0\" class=\"so-panel widget widget_text panel-first-child panel-last-child\" data-index=\"0\" >\t\t\t<div class=\"textwidget\"><p><\/p>\n<p><strong>Name: <\/strong>Krishna Gopal Dhal<\/p>\n<p><strong>Affiliation: <\/strong>Assistant Professor, Midnapur College<\/p>\n<p><strong>Title: Partitional Clustering based Fast and Robust Digital Pathology Image Segmentation<\/strong><\/p>\n<p> <\/p>\n<p><strong>Area:<\/strong> Biomedical Signal and Image Processing<\/p>\n<p><\/p>\n<\/div>\n\t\t<\/div><\/div><div id=\"pgc-gb988-69f0505aded16-0-1\"  class=\"panel-grid-cell\" ><div id=\"panel-gb988-69f0505aded16-0-1-0\" class=\"so-panel widget widget_text panel-first-child panel-last-child\" data-index=\"1\" >\t\t\t<div class=\"textwidget\"><p><strong>Abstract:<\/strong> Accurate segmentation of different regions of digital pathology images is of the utmost importance for a Computer Aided Diagnosis (CAD) system. Pathology image segmentation techniques must be fast, accurate, and noise-robust. Partitional clustering techniques like K-Means (KM) and Fuzzy C-Means (FCM) can be enhanced to fulfil the mentioned needs. Image histogram-based or superpixel image-based clustering techniques can be very useful to perform pathology image segmentation. Finding and representing the histogram of colour images is a hard task, and classical histogram-based clustering techniques are not noise-robust. Hence, superpixel image-based clustering techniques currently attract the interest of researchers. A superpixel image helps to reduce the execution time of the clustering technique and also has noise-resistance. The local optima trapping problem of the KM and FCM can be overcome to some extent by using nature-inspired optimizers (NIO) like particle swarm optimizer (PSO). Recently, researchers have also been working in this domain, i.e., NIO-based clustering techniques for digital pathology image segmentation.<\/p>\n<\/div>\n\t\t<\/div><\/div><\/div><\/div>\n\n\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Assistant Professor<br \/>\nMidnapur College<\/p>\n","protected":false},"author":1,"featured_media":982,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-988","page","type-page","status-publish","has-post-thumbnail","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Krishna Gopal Dhal - Digital Health Symposium and Roundtable<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"http:\/\/digital-health.one\/roundtable\/2023\/krishna-gopal-dhal\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Krishna Gopal Dhal - 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