{"id":232717,"updated":"2025-01-19T10:20:39.097746+00:00","links":{},"created":"2025-01-19T01:33:44.579743+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232717","sets":["1164:4619:11539:11552"]},"path":["11552"],"owner":"44499","recid":"232717","title":["MR画像分類における腫瘍の位置情報の有用性評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-25"},"_buckets":{"deposit":"33ca0f5d-af6c-4ca9-9cd1-588d8615d8da"},"_deposit":{"id":"232717","pid":{"type":"depid","value":"232717","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"MR画像分類における腫瘍の位置情報の有用性評価","author_link":["630649","630652","630650","630653","630648","630651"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"MR画像分類における腫瘍の位置情報の有用性評価"},{"subitem_title":"Assessment of the Utility of Tumor Location Information in MR Image Classification","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2024-02-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"九州大学大学院システム情報科学府"},{"subitem_text_value":"九州大学大学院システム情報科学研究院"},{"subitem_text_value":"九州大学大学院システム情報科学研究院"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Electrical Engineering，Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Information Science and Electrical Engineering, Kyushu University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/232717/files/IPSJ-CVIM24237026.pdf","label":"IPSJ-CVIM24237026.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24237026.pdf","filesize":[{"value":"1.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"e5284c8c-267b-473d-bebc-446f70771443","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"西中川, 司"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"武石, 啓成"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"竹内, 純一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tsukasa, Nishinakagawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoshinari, Takeishi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jun’ichi, Takeuchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"MRI とは，体内の水素原子核の磁気共鳴現象を利用して，体の断面画像を得るものであり，現在多くの医療現場で用いられている．本研究では，腫瘍を有する頭部の MR 画像を入力として，腫瘍の種類を，ニューラルネットを用いて分類する問題について考察する．こうした分類が高精度で可能になれば，臨床における自動診断に役立つことが期待されるが，MR 画像分類には学習に利用できる実データが不足している課題がある．それを解決するために，本研究では既存のモデルを利用するファインチューニングを行い，限られたデータから高精度なモデルを作成した．また，腫瘍は種類によって発生する位置の分布が異なるため，腫瘍の形状だけではなく，その位置情報も利用することで MR 画像分類の性能の向上が可能であるかについて，公開された MR 画像とそれらを劣化させた画像を利用した実験により評価した．その結果，画像を劣化させるにつれ，位置情報の有用性が高まることを確認することができた．その際，腫瘍の位置情報を 2 次元の座標ベクトルで与えるよりも，画像として与える方が位置情報の有用性が高いことも確認できた．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"26","bibliographicVolumeNumber":"2024-CVIM-237"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}