{"id":3895,"date":"2011-05-13T13:06:38","date_gmt":"2011-05-13T13:06:38","guid":{"rendered":"http:\/\/hgpu.org\/?p=3895"},"modified":"2011-05-13T13:06:38","modified_gmt":"2011-05-13T13:06:38","slug":"fast-katsevich-algorithm-based-on-gpu-for-helical-cone-beam-computed-tomography","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=3895","title":{"rendered":"Fast Katsevich Algorithm Based on GPU for Helical Cone-Beam Computed Tomography"},"content":{"rendered":"<p>Katsevich reconstruction algorithm represents a breakthrough for helical cone-beam computed tomography (CT) reconstruction, because it is the first exact cone-beam reconstruction algorithm of filtered backprojection (FBP) type with 1-D shift-invariant filtering. Although FBP-type reconstruction algorithm is effective, 3-D CT reconstruction is time-consuming, and the accelerations of Katsevich algorithm on CPU or cluster have been widely studied. In this paper, Katsevich algorithm is accelerated by using graphics processing unit, including flat-detector and curved-detector geometry in the case of helical orbit. An overscan formula is derived, which helps to avoid unnecessary overscan in practical CT scanning. Based on the overscan formula, a volume-blocking method in device memory is proposed. One advantage of the blocking method is that it can reconstruct large volume with high speed.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Katsevich reconstruction algorithm represents a breakthrough for helical cone-beam computed tomography (CT) reconstruction, because it is the first exact cone-beam reconstruction algorithm of filtered backprojection (FBP) type with 1-D shift-invariant filtering. Although FBP-type reconstruction algorithm is effective, 3-D CT reconstruction is time-consuming, and the accelerations of Katsevich algorithm on CPU or cluster have been widely [&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":[33,38,3],"tags":[444,479,478,1786,512,1788,20,183,182,567],"class_list":["post-3895","post","type-post","status-publish","format-standard","hentry","category-image-processing","category-medicine","category-paper","tag-cg","tag-computed-tomography","tag-ct","tag-image-processing","tag-image-reconstruction","tag-medicine","tag-nvidia","tag-nvidia-geforce-8800-gtx","tag-opengl","tag-tomography"],"views":2374,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3895","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=3895"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3895\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3895"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3895"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3895"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}