{"created":"2023-12-14T01:49:11.928577+00:00","id":2000204,"links":{},"metadata":{"_buckets":{"deposit":"4551930e-4cf2-4255-82de-9c92f8e4ff15"},"_deposit":{"created_by":15,"id":"2000204","owner":"15","owners":[15],"pid":{"revision_id":0,"type":"depid","value":"2000204"},"status":"published"},"_oai":{"id":"oai:mie-u.repo.nii.ac.jp:02000204","sets":["334:627:1701929182893"]},"author_link":[],"control_number":"2000204","item_8_biblio_info_6":{"attribute_name":"bibliographic_information","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2022-05-25","bibliographicIssueDateType":"Issued"}}]},"item_8_description_14":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"本研究では、正常ボランティアにて、冠動脈MRA撮影の高速化技術の最適化を行い、冠動脈MRAの高画質化を畳み込みニューラルネットワーク(CNN)を使った画像処理技術にて達成した。 また、侵襲的冠動脈造影（ICA）による冠動脈狭窄度を冠動脈MRA画像から診断するような人工知能による画像処理技術の開発について検討した。 予備試験では、高い診断能が示されたが最適化の余地があり検討を継続する予定である。","subitem_description_type":"Abstract"},{"subitem_description":"In this study, the authors optimized a speedup technique for coronary MRA imaging in healthy volunteers and achieve high image quality of coronary MRA using convolutional neural network (CNN) -based image processing techniques. The artificial intelligence-based image processing techniques for diagnosing the stenosis on coronary MRA was investigated using invasive coronary angiography (ICA) as a reference. Preliminary tests showed high diagnostic performance, but there is room for optimization and further research is planned.","subitem_description_type":"Abstract"}]},"item_8_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"2018年度～2021年度科学研究費補助金(基盤研究(C))研究成果報告書","subitem_description_type":"Other"}]},"item_8_description_64":{"attribute_name":"科研費番号","attribute_value_mlt":[{"subitem_description":"18K07749","subitem_description_type":"Other"}]},"item_8_publisher_30":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"三重大学"}]},"item_8_text_31":{"attribute_name":"出版者（ヨミ）","attribute_value_mlt":[{"subitem_text_value":"ミエダイガク"}]},"item_8_text_65":{"attribute_name":"item_8_text_65","attribute_value_mlt":[{"subitem_text_value":"Kaken / 科研費報告書"}]},"item_8_version_type_15":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"佐久間, 肇","creatorNameLang":"ja"},{"creatorName":"Sakuma, Hajime","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"石田, 正樹","creatorNameLang":"ja"},{"creatorName":"Ishida, Masaki","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"中山, 良平","creatorNameLang":"ja"},{"creatorName":"Nakayama, Ryohei","creatorNameLang":"en"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2023-12-14"}],"filename":"2023RP0042.pdf","filesize":[{"value":"617 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"url":"https://mie-u.repo.nii.ac.jp/record/2000204/files/2023RP0042.pdf"},"version_id":"0703d36b-efd0-47f9-baf0-6177e2b17c24"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"冠動脈疾患","subitem_subject_scheme":"Other"},{"subitem_subject":"冠動脈MRA","subitem_subject_scheme":"Other"},{"subitem_subject":"人工知能","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"item_resource_type","attribute_value_mlt":[{"resourcetype":"research report","resourceuri":"http://purl.org/coar/resource_type/c_18ws"}]},"item_title":"人工知能により冠動脈MRAから冠血流予備量比を計測するMR-FFR法の開発","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"人工知能により冠動脈MRAから冠血流予備量比を計測するMR-FFR法の開発","subitem_title_language":"ja"},{"subitem_title":"Prediction of FFR from coronary MRA using deep learning","subitem_title_language":"en"}]},"item_type_id":"8","owner":"15","path":["1701929182893"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-12-14"},"publish_date":"2023-12-14","publish_status":"0","recid":"2000204","relation_version_is_last":true,"title":["人工知能により冠動脈MRAから冠血流予備量比を計測するMR-FFR法の開発"],"weko_creator_id":"15","weko_shared_id":-1},"updated":"2024-09-24T01:40:39.963120+00:00"}