{"id":7168,"date":"2012-02-18T20:38:08","date_gmt":"2012-02-18T18:38:08","guid":{"rendered":"http:\/\/hgpu.org\/?p=7168"},"modified":"2012-02-18T20:38:08","modified_gmt":"2012-02-18T18:38:08","slug":"cone-beam-computed-tomography-image-reconstruction-based-on-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=7168","title":{"rendered":"Cone-beam Computed tomography image reconstruction based on GPU"},"content":{"rendered":"<p>As so long, three-dimensional cone-beam computed tomography(CBCT) image reconstruction is a hot issue in medical imaging field. Often the computation operation of CBCT reconstruction is huge and the reconstruction time is long. Now with the development of computer technology, especially the rapid development of Graphics Processing Unit (GPU) based general-purpose computing technology enables fast CBCT reconstruction possible. In this paper, a CBCT reconstruction algorithm-ordered subset expectation maximization (OSEM) based on GPU is developed. Experiment on the Shepp-logan phantom model showed that a good speedup is received.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>As so long, three-dimensional cone-beam computed tomography(CBCT) image reconstruction is a hot issue in medical imaging field. Often the computation operation of CBCT reconstruction is huge and the reconstruction time is long. Now with the development of computer technology, especially the rapid development of Graphics Processing Unit (GPU) based general-purpose computing technology enables fast CBCT [&hellip;]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[36,89,38,3],"tags":[1787,479,478,14,512,1788,20,1264,567],"class_list":["post-7168","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-medicine","category-paper","tag-algorithms","tag-computed-tomography","tag-ct","tag-cuda","tag-image-reconstruction","tag-medicine","tag-nvidia","tag-nvidia-geforce-gt-240-m","tag-tomography"],"views":2697,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7168","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/users\/351"}],"replies":[{"embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=7168"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/7168\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=7168"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=7168"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=7168"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}