{"id":690,"date":"2012-02-01T10:09:46","date_gmt":"2012-02-01T15:09:46","guid":{"rendered":"https:\/\/my.dev.vanderbilt.edu\/masi\/?p=690"},"modified":"2016-11-01T10:12:30","modified_gmt":"2016-11-01T15:12:30","slug":"finding-seeds-for-segmentation-using-statistical-fusion","status":"publish","type":"post","link":"https:\/\/my.dev.vanderbilt.edu\/masi\/2012\/02\/finding-seeds-for-segmentation-using-statistical-fusion\/","title":{"rendered":"Finding Seeds for Segmentation Using Statistical Fusion"},"content":{"rendered":"<p>Fangxu Xing, Andrew J. Asman, Jerry L. Prince, Bennett A. Landman. \u201cFinding Seeds for Segmentation Using Statistical Fusion.\u201d In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2012<\/p>\n<p>Full text:\u00a0<a href=\"https:\/\/www.ncbi.nlm.nih.gov\/pubmed\/23019385\">https:\/\/www.ncbi.nlm.nih.gov\/pubmed\/23019385<\/a><\/p>\n<h2>Abstract<\/h2>\n<p>Image labeling is an essential step for quantitative analysis of medical images. Many image labeling algorithms require seed identification in order to initialize segmentation algorithms such as region growing, graph cuts, and the random walker. Seeds are usually placed manually by human raters, which makes these algorithms semi-automatic and can be prohibitive for very large datasets. In this paper an automatic algorithm for placing seeds using multi-atlas registration and statistical fusion is proposed. Atlases containing the centers of mass of a collection of neuroanatomical objects are deformably registered in a training set to determine where these centers of mass go after labels transformed by registration. The biases of these transformations are determined and incorporated in a continuous form of Simultaneous Truth And Performance Level Estimation (STAPLE) fusion, thereby improving the estimates (on average) over a single registration strategy that does not incorporate bias or fusion. We evaluate this technique using real 3D brain MR image atlases and demonstrate its efficacy on correcting the data bias and reducing the fusion error.<br \/>\n<img loading=\"lazy\" decoding=\"async\" class=\"alignnone wp-image-691\" src=\"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-content\/uploads\/sites\/2304\n2661\/2016\/11\/nihms342360f2.jpg\" alt=\"NIHMS342360.html\" width=\"500\" height=\"411\" \/><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Fangxu Xing, Andrew J. Asman, Jerry L. Prince, Bennett A. Landman. \u201cFinding Seeds for Segmentation Using Statistical Fusion.\u201d In Proceedings of the SPIE Medical Imaging Conference. San Diego, California, February 2012 Full text:\u00a0https:\/\/www.ncbi.nlm.nih.gov\/pubmed\/23019385 Abstract Image labeling is an essential step for quantitative analysis of medical images. Many image labeling algorithms require seed identification in order&#8230;<\/p>\n","protected":false},"author":2823,"featured_media":691,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[46,4],"tags":[42],"class_list":["post-690","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-multi-atlas-segmentation","category-neuroimaging","tag-staple"],"_links":{"self":[{"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts\/690","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/users\/2823"}],"replies":[{"embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/comments?post=690"}],"version-history":[{"count":1,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts\/690\/revisions"}],"predecessor-version":[{"id":694,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts\/690\/revisions\/694"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/media\/691"}],"wp:attachment":[{"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/media?parent=690"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/categories?post=690"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/tags?post=690"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}