{"id":5646,"date":"2011-09-22T19:31:26","date_gmt":"2011-09-22T16:31:26","guid":{"rendered":"http:\/\/hgpu.org\/?p=5646"},"modified":"2011-09-22T19:31:26","modified_gmt":"2011-09-22T16:31:26","slug":"acceleration-of-the-speed-of-tissue-characterization-algorithm-for-coronary-plaque-by-employing-gpgpu-technique","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=5646","title":{"rendered":"Acceleration of the speed of tissue characterization algorithm for coronary plaque by employing GPGPU technique"},"content":{"rendered":"<p>The general purpose computation technique on Graphics Processing Unit (GPGPU) has got into the limelight recently. The authors have proposed the multiple k-nearest neighbor (MkNN) classifier for the tissue characterization of coronary plaque. Its characterization performance is highly evaluated. The purpose of this paper is to accelerate the speed of MkNN classifier aiming for it to be actually used in the medical practice. It has been confirmed that its speed is drastically accelerated enough for the practical use.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The general purpose computation technique on Graphics Processing Unit (GPGPU) has got into the limelight recently. The authors have proposed the multiple k-nearest neighbor (MkNN) classifier for the tissue characterization of coronary plaque. Its characterization performance is highly evaluated. The purpose of this paper is to accelerate the speed of MkNN classifier aiming for it [&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":[1787,14,1788,349,20,188,199],"class_list":["post-5646","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-medicine","category-paper","tag-algorithms","tag-cuda","tag-medicine","tag-nearest-neighbour","tag-nvidia","tag-surgical-simulation","tag-tesla-c1060"],"views":2212,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5646","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=5646"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/5646\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=5646"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=5646"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=5646"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}