Clinical diagnosis and quantification of liver disease have been improved through the development of techniques using contrast-enhanced liver MRI sequences. To qualitatively or quantitatively analyze such image sequences, one first needs to correct for rigid and non-rigid motion of the liver. For motion correction of the liver, we have employed bi-directional local correlation coefficient Demons, which is a variation of the original Demons method. However, despite the intrinsic speed of the Demons method, the run-time on the order of an hour of its CPU-based implementation is not sufficiently short for a regular clinical use. For this reason we implemented the method on a graphics processing unit (GPU) using OpenCL. On NVIDIA GTX 260M, which is a laptop GPU, we achieved sub-minute runtime for the motion correction of typical liver MRI scans, which was ~50 times faster than its CPU-based implementation. A sub-minute runtime of liver MRI motion correction allows for its regular clinical use.<\/p>\n","protected":false},"excerpt":{"rendered":"
Clinical diagnosis and quantification of liver disease have been improved through the development of techniques using contrast-enhanced liver MRI sequences. To qualitatively or quantitatively analyze such image sequences, one first needs to correct for rigid and non-rigid motion of the liver. For motion correction of the liver, we have employed bi-directional local correlation coefficient Demons, […]<\/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":[38,90,3],"tags":[512,1788,807,20,1115,1793],"class_list":["post-4420","post","type-post","status-publish","format-standard","hentry","category-medicine","category-opencl","category-paper","tag-image-reconstruction","tag-medicine","tag-mri","tag-nvidia","tag-nvidia-geforce-gtx-260-m","tag-opencl"],"views":2323,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4420","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=4420"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/4420\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=4420"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=4420"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=4420"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}