{"id":1849,"date":"2010-12-05T09:20:38","date_gmt":"2010-12-05T09:20:38","guid":{"rendered":"http:\/\/hgpu.org\/?p=1849"},"modified":"2010-12-05T09:20:38","modified_gmt":"2010-12-05T09:20:38","slug":"interactive-physically-based-x-ray-simulation-cpu-or-gpu","status":"publish","type":"post","link":"https:\/\/hgpu.org\/?p=1849","title":{"rendered":"Interactive physically-based X-ray simulation: CPU or GPU?"},"content":{"rendered":"<p>Interventional Radiology (IR) procedures are minimally invasive, targeted treatments performed using imaging for guidance. Needle puncture using ultrasound, x-ray, or computed tomography (CT) images is a core task in the radiology curriculum, and we are currently developing a training simulator for this. One requirement is to include support for physically-based simulation of x-ray images from CT data sets. In this paper, we demonstrate how to exploit the capability of today&#8217;s graphics cards to efficiently achieve this on the Graphics Processing Unit (GPU) and compare performance with an efficient software only implementation using the Central Processing Unit (CPU).<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Interventional Radiology (IR) procedures are minimally invasive, targeted treatments performed using imaging for guidance. Needle puncture using ultrasound, x-ray, or computed tomography (CT) images is a core task in the radiology curriculum, and we are currently developing a training simulator for this. One requirement is to include support for physically-based simulation of x-ray images from [&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":[479,1786,1788,20,895,420,182,144],"class_list":["post-1849","post","type-post","status-publish","format-standard","hentry","category-image-processing","category-medicine","category-paper","tag-computed-tomography","tag-image-processing","tag-medicine","tag-nvidia","tag-nvidia-geforce-6400","tag-nvidia-quadro-fx-3400","tag-opengl","tag-rendering"],"views":2163,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1849","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=1849"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/1849\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1849"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1849"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1849"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}