{"id":4073,"date":"2011-05-20T07:54:28","date_gmt":"2011-05-20T07:54:28","guid":{"rendered":"http:\/\/hgpu.org\/?p=4073"},"modified":"2011-05-20T07:54:28","modified_gmt":"2011-05-20T07:54:28","slug":"gpu-accelerated-alignment-of-3-d-cta-with-2-d-x-ray-data-for-improved-guidance-in-coronary-interventions","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=4073","title":{"rendered":"GPU accelerated alignment of 3-D CTA with 2-D X-ray data for improved guidance in coronary interventions"},"content":{"rendered":"<p>This paper presents a 2-D\/3-D registration method for the alignment of cardiac X-ray images to ECG gated CTA data of the coronary arteries. The purpose of our work is to provide visualization of instruments in relation to pre-operative CTA data during interventional cardiology for improved image guidance, especially in complex procedures. The method utilizes the graphical processing unit (GPU) for rendering of digitally reconstructed radiographs (DRRs) from a 3-D CTA-derived coronary model. Using a multi-scale gradient ascent framework, the normalized cross correlation between the simulated and real X-ray image is optimized. Quantitative evaluation is performed by computing the projection error of the vessel centerlines, which was oPn average 1.34 mm.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>This paper presents a 2-D\/3-D registration method for the alignment of cardiac X-ray images to ECG gated CTA data of the coronary arteries. The purpose of our work is to provide visualization of instruments in relation to pre-operative CTA data during interventional cardiology for improved image guidance, especially in complex procedures. The method utilizes the [&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":[36,33,38,3],"tags":[1787,216,858,686,1786,365,1788,144],"class_list":["post-4073","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-image-processing","category-medicine","category-paper","tag-algorithms","tag-computed-radiography","tag-heart","tag-image-alignment","tag-image-processing","tag-image-registration","tag-medicine","tag-rendering"],"views":2217,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4073","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=4073"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4073\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4073"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4073"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4073"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}