{"id":251,"date":"2019-10-23T08:14:00","date_gmt":"2019-10-23T08:14:00","guid":{"rendered":"http:\/\/www.cs.ubbcluj.ro\/~meco\/?p=251"},"modified":"2026-02-01T12:09:19","modified_gmt":"2026-02-01T12:09:19","slug":"extended-region-growing-algorithm-for-whole-heart-segmentation-from-cardiac-mri-images-2019","status":"publish","type":"post","link":"https:\/\/www.cs.ubbcluj.ro\/~meco\/extended-region-growing-algorithm-for-whole-heart-segmentation-from-cardiac-mri-images-2019\/","title":{"rendered":"Extended region growing algorithm for whole heart segmentation from cardiac MRI images (2019)"},"content":{"rendered":"\n<h3 class=\"wp-block-heading\">Abstract<\/h3>\n\n\n\n<p>We aimed to assess the reliability of an automatic solution for whole-heart segmentation of MRI images of patients with atrial fibrillation (AF). We propose a semi-interactive image segmentation algorithm based on region growing, GrowCut1, using novel neighborhood structures based on Cellular Automata. We complemented the algorithm with a global view of the signal using remote neighbors outside standard neighborhoods (Moore and Von Neumann). We validated the proposed semi-interactive algorithm on a clinical dataset from our AtFib study.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Citare<\/h3>\n\n\n\n<p>Marginean, R., Popa, L., Coman, M., Manole, S., Coman, V., Andreica, A., Diosan, L., B\u00e1lint, Z., Extended region growing algorithm for whole heart segmentation from cardiac MRI images, ESCR 2019, 2019, accepted&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We aimed to assess the reliability of an automatic solution for whole-heart segmentation of MRI images of patients with atrial fibrillation (AF). We propose a semi-interactive image segmentation algorithm based on region growing, GrowCut1, using novel neighborhood structures based on Cellular Automata. We complemented the algorithm with a global view of the signal using remote neighbors outside standard neighborhoods (Moore and Von Neumann). We validated the proposed semi-interactive algorithm on a clinical dataset from our AtFib study.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[10,11],"_links":{"self":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/251"}],"collection":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/comments?post=251"}],"version-history":[{"count":2,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/251\/revisions"}],"predecessor-version":[{"id":1554,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/posts\/251\/revisions\/1554"}],"wp:attachment":[{"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/media?parent=251"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/categories?post=251"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cs.ubbcluj.ro\/~meco\/wp-json\/wp\/v2\/tags?post=251"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}