{"id":1971,"date":"2010-12-11T21:40:01","date_gmt":"2010-12-11T21:40:01","guid":{"rendered":"http:\/\/hgpu.org\/?p=1971"},"modified":"2010-12-11T21:40:01","modified_gmt":"2010-12-11T21:40:01","slug":"real-time-stereographic-rendering-and-display-of-medical-images-with-programmable-gpus","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=1971","title":{"rendered":"Real-time stereographic rendering and display of medical images with programmable GPUs"},"content":{"rendered":"<p>The study was to explore the power and feasibility of using programmable graphics processing units (GPUs) for real-time rendering and displaying large 3D medical datasets for stereoscopic display workstation. Lung cancer screening CT images were used for developing GPU-based stereo rendering and displaying. The study was run on a personal computer with a 128 MB NVIDIA Quadro FX 1100 graphics card. The performance of rendering and displaying was measured and compared between GPU-based and central processing unit (CPU)-based programming. The results indicate that GPU-based programming was capable of rendering large 3D datasets at real-time interactive rates with stereographic displays.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The study was to explore the power and feasibility of using programmable graphics processing units (GPUs) for real-time rendering and displaying large 3D medical datasets for stereoscopic display workstation. Lung cancer screening CT images were used for developing GPU-based stereo rendering and displaying. The study was run on a personal computer with a 128 MB [&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":[479,478,1786,1788,20,908,182,297,144],"class_list":["post-1971","post","type-post","status-publish","format-standard","hentry","category-image-processing","category-medicine","category-paper","tag-computed-tomography","tag-ct","tag-image-processing","tag-medicine","tag-nvidia","tag-nvidia-quadro-fx-1100","tag-opengl","tag-real-time-graphics","tag-rendering"],"views":2014,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1971","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=1971"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1971\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1971"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1971"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1971"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}