We developed a GPU-based real-time imaging software suite for medical ultrasound imaging to provide a fast real-time imaging platform for various probe geometries and imaging schemes. The imaging software receives raw RF data from a data acquisition system, and processes them on GPU to reconstruct real-time images. The most general-purpose imaging program in the suite displays three cross-sectional images for arbitrary probe geometry and various imaging schemes including conventional beamforming, synthetic beamforming, and planewave compounding. The other imaging programs in the software suite, derived from the general-purpose imaging program, are optimized for their own purposes, such as displaying a rotating B-mode plane and its maximum intensity projection (MIP), photoacoustic imaging, and real-time volume-rendering. Real-time imaging was successfully demonstrated using each of the imaging programs in the software suite.<\/p>\n","protected":false},"excerpt":{"rendered":"
We developed a GPU-based real-time imaging software suite for medical ultrasound imaging to provide a fast real-time imaging platform for various probe geometries and imaging schemes. The imaging software receives raw RF data from a data acquisition system, and processes them on GPU to reconstruct real-time images. The most general-purpose imaging program in the suite […]<\/p>\n","protected":false},"author":351,"featured_media":0,"comment_status":"open","ping_status":"closed","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":[89,33,3],"tags":[14,764,1786,20,144,1006,208],"class_list":["post-10261","post","type-post","status-publish","format-standard","hentry","category-nvidia-cuda","category-image-processing","category-paper","tag-cuda","tag-data-acquisition","tag-image-processing","tag-nvidia","tag-rendering","tag-tesla-c2070","tag-ultrasound"],"views":2734,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10261","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=10261"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/10261\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10261"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10261"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10261"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}