Breast Microwave Radar(BMR) is a novel imaging modality that is capable of producing high contrast images and can detect tumors of at least 4mm. To properly visualize the responses from the breast structures, BMR data sets must be reconstructed. In this paper, a real time BMR image formation technique is proposed. This approach is based on the use of a Single Instruction Multiple Thread(SIMT) interpolation method. By using this programming model, the proposed approach can be implemented on General Purpose Graphic Processing Unit (GPGPU) platform to speed up the reconstruction process. The proposed method yielded promising results when applied to simulated data sets obtained using anatomically accurate numeric phantoms. In average, the proposed approach yielded speed increases of one order of magnitude compared to its CPU counterpart, and two orders of magnitude with respect to current BMR reconstruction techniques.<\/p>\n","protected":false},"excerpt":{"rendered":"
Breast Microwave Radar(BMR) is a novel imaging modality that is capable of producing high contrast images and can detect tumors of at least 4mm. To properly visualize the responses from the breast structures, BMR data sets must be reconstructed. In this paper, a real time BMR image formation technique is proposed. This approach is based […]<\/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":[36,89,33,38,3],"tags":[1787,14,1786,512,172,1788,807,20],"class_list":["post-3708","post","type-post","status-publish","format-standard","hentry","category-algorithms","category-nvidia-cuda","category-image-processing","category-medicine","category-paper","tag-algorithms","tag-cuda","tag-image-processing","tag-image-reconstruction","tag-magnetic-resonance-imaging","tag-medicine","tag-mri","tag-nvidia"],"views":2128,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3708","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=3708"}],"version-history":[{"count":0,"href":"https:\/\/hgpu.org\/index.php?rest_route=\/wp\/v2\/posts\/3708\/revisions"}],"wp:attachment":[{"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3708"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3708"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/hgpu.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3708"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}