{"created":"2023-05-15T14:51:26.408796+00:00","id":70317,"links":{},"metadata":{"_buckets":{"deposit":"7cf623cd-545c-4177-9e66-20cb5fd7721f"},"_deposit":{"created_by":1,"id":"70317","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"70317"},"status":"published"},"_oai":{"id":"oai:repo.qst.go.jp:00070317","sets":["10:28"]},"author_link":["690449","690450","690454","690455","690452","690451","690447","690453","690446","690445","690448","690456"],"item_10005_date_7":{"attribute_name":"発表年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2010-11-06","subitem_date_issued_type":"Issued"}]},"item_10005_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"The OpenPET, which have a physically opened space between two detector rings, is our new geometry to enable PET imaging during radiation therapy. Especially, tracking a moving target such as a tumor in the lung will become possible if the real-time imaging system is realized. In this paper, therefore, we developed a list-mode image reconstruction method using general purpose graphic processing units (GPGPUs). We used the list-mode dynamic row-action maximum likelihood algorithm (DRAMA) with new relaxation parameter calculated by the vector of image update. For GPU implementation, the efficiency of acceleration depends on the implementation method which is required to avoid conditional statements and to use efficient memory accesses. We developed a system model in which each element of system matrix is calculated as the value of detector response function (DRF) of the length between the center of a voxel and a line of response (LOR). The system model was suited to GPU implementations that enable us to calculate each element of the system matrix with reduced number of the conditional statements. We applied the developed method to a small OpenPET prototype, which was developed for a proof-of-concept. We measured the micro-Derenzo phantom placed at the gap. The results showed that the same quality of reconstructed images using GPU as using CPU were achieved, and calculation speed on the GPU was 35.5 times faster than that on the CPU.","subitem_description_type":"Abstract"}]},"item_10005_description_6":{"attribute_name":"会議概要（会議名, 開催地, 会期, 主催者等）","attribute_value_mlt":[{"subitem_description":"2010 Nuclear Science Symposium and Medical Imaging Conference","subitem_description_type":"Other"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"metadata only access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_14cb"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kinouchi, Shoko"}],"nameIdentifiers":[{"nameIdentifier":"690445","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Yamaya, Taiga"}],"nameIdentifiers":[{"nameIdentifier":"690446","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Yoshida, Eiji"}],"nameIdentifiers":[{"nameIdentifier":"690447","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Tashima, Hideaki"}],"nameIdentifiers":[{"nameIdentifier":"690448","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Kudo, Hiroyuki"}],"nameIdentifiers":[{"nameIdentifier":"690449","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Suga, Mikio"}],"nameIdentifiers":[{"nameIdentifier":"690450","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"木内 尚子","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"690451","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"山谷 泰賀","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"690452","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"吉田 英治","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"690453","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"田島 英朗","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"690454","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"工藤 博幸","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"690455","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"菅 幹生","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"690456","nameIdentifierScheme":"WEKO"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"conference object","resourceuri":"http://purl.org/coar/resource_type/c_c94f"}]},"item_title":"GPU Implementation of List-mode DRAMA for Real-time OpenPET Image Reconstruction","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"GPU Implementation of List-mode DRAMA for Real-time OpenPET Image Reconstruction"}]},"item_type_id":"10005","owner":"1","path":["28"],"pubdate":{"attribute_name":"公開日","attribute_value":"2010-11-11"},"publish_date":"2010-11-11","publish_status":"0","recid":"70317","relation_version_is_last":true,"title":["GPU Implementation of List-mode DRAMA for Real-time OpenPET Image Reconstruction"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-15T20:04:20.157560+00:00"}