{"id":695,"date":"2011-09-01T10:12:55","date_gmt":"2011-09-01T15:12:55","guid":{"rendered":"https:\/\/my.dev.vanderbilt.edu\/masi\/?p=695"},"modified":"2016-11-01T10:21:20","modified_gmt":"2016-11-01T15:21:20","slug":"695","status":"publish","type":"post","link":"https:\/\/my.dev.vanderbilt.edu\/masi\/2011\/09\/695\/","title":{"rendered":"Estimation of Registration Accuracy Applied to Multi-Atlas Segmentation"},"content":{"rendered":"

R. Datteri, A. Asman, B. Landman, and B. Dawant. \u201cEstimation of Registration Accuracy Applied to Multi-Atlas Segmentation.\u201d In . Toronto, Canada, September 2011 (Oral Presentation)<\/p>\n

Full text:\u00a0http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.728.4212&rep=rep1&type=pdf<\/a><\/strong><\/p>\n

Abstract<\/h2>\n
Multi-atlas registration-based segmentation has recently become a<\/div>\n
popular technique in medical imaging. Since the quality of individual atlas<\/div>\n
segmentations affect the quality of the results, atlas selection and atlas fusion<\/div>\n
have become important areas of research for multi-atlas segmentation. In this<\/div>\n
paper, we present an automatic technique that approximately calculates the<\/div>\n
quality of registration. We applied our method to multi-atlas segmentation and<\/div>\n
find that our measure correlates strongly ( = 0.79) with the ground truth<\/div>\n
DICE similarity index. When applied to atlas fusion using a majority vote<\/div>\n
technique weighted by our measure of registration quality, our algorithm<\/div>\n
performs statistically better than both an un-weighted majority vote technique<\/div>\n
and a voting technique weighted by residual normalized mutual information.<\/div>\n
<\/div>\n

\"aaa\"<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

R. Datteri, A. Asman, B. Landman, and B. Dawant. \u201cEstimation of Registration Accuracy Applied to Multi-Atlas Segmentation.\u201d In . Toronto, Canada, September 2011 (Oral Presentation) Full text:\u00a0http:\/\/citeseerx.ist.psu.edu\/viewdoc\/download?doi=10.1.1.728.4212&rep=rep1&type=pdf Abstract Multi-atlas registration-based segmentation has recently become a popular technique in medical imaging. Since the quality of individual atlas segmentations affect the quality of the results, atlas selection…<\/p>\n","protected":false},"author":2823,"featured_media":711,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[46,4,65],"tags":[12],"class_list":["post-695","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-multi-atlas-segmentation","category-neuroimaging","category-registration","tag-multi-atlas"],"_links":{"self":[{"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts\/695","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=695"}],"version-history":[{"count":3,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts\/695\/revisions"}],"predecessor-version":[{"id":714,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/posts\/695\/revisions\/714"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/media\/711"}],"wp:attachment":[{"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/media?parent=695"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/categories?post=695"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/my.dev.vanderbilt.edu\/masi\/wp-json\/wp\/v2\/tags?post=695"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}