{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00226474","sets":["1164:2735:11166:11285"]},"path":["11285"],"owner":"44499","recid":"226474","title":["High Resolution SegFormerに基づく脊椎のセマンティックセグメンテーション"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-06-22"},"_buckets":{"deposit":"2da3ea0a-584a-4db3-8678-7c370910743b"},"_deposit":{"id":"226474","pid":{"type":"depid","value":"226474","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"High Resolution SegFormerに基づく脊椎のセマンティックセグメンテーション","author_link":["601367","601368","601370","601369"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"High Resolution SegFormerに基づく脊椎のセマンティックセグメンテーション"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"数理モデル化と問題解決1","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2023-06-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"同志社大学大学院理工学研究科"},{"subitem_text_value":"同志社大学大学院理工学研究科"},{"subitem_text_value":"同志社大学理工学部"},{"subitem_text_value":"龍谷大学先端理工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Science and Engineering, Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Engineering, Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Science and Engineering, Doshisha University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Advanced Science and Technology, Ryukoku 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/226474/files/IPSJ-MPS23143006.pdf","label":"IPSJ-MPS23143006.pdf"},"date":[{"dateType":"Available","dateValue":"2025-06-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS23143006.pdf","filesize":[{"value":"1.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"bde6e4a8-84da-4724-9ec6-0e35c0a7ad32","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"増田, 尚大"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"深尾, 賢太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小野, 景子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田原, 大輔"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","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":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"医療画像において脊椎のように，複雑な構造をしている部位を抽出するためには，高精度な領域抽出が必要であり，セマンティックセグメンテーションが用いられる．セマンティックセグメンテーションは画像のチャネル数を増加させ，CNN を用いて複雑な特徴を抽出可能にすることが一般的だが，画像内の位置情報を考慮した領域抽出が容易でない．そこで，本研究では画像内の位置情報を考慮することで画像細部の特徴に注目した画像分類が可能な SegFormer を用いて医療画像における領域抽出精度の向上を目指す．具体的には，SegFormer のモデルを改良し，畳み込み層の追加と特徴量マップの高解像度化を施した場合における抽出精度の向上を目指す．結果，畳み込み層の追加は抽出対象の輪郭の特徴を捉えることが可能であることが分かり，特徴量マップの高解像度化は IoU を大きく上昇させることが分かった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"2","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2023-06-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"6","bibliographicVolumeNumber":"2023-MPS-143"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":226474,"updated":"2025-01-19T12:27:57.949730+00:00","links":{},"created":"2025-01-19T01:25:55.414306+00:00"}