{"created":"2023-05-15T14:44:50.073845+00:00","id":61282,"links":{},"metadata":{"_buckets":{"deposit":"3e5b0df0-0b14-4c1e-bf6a-ef6a8134a475"},"_deposit":{"created_by":1,"id":"61282","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"61282"},"status":"published"},"_oai":{"id":"oai:repo.qst.go.jp:00061282","sets":["10:29"]},"author_link":["606616","606621","606615","606623","606617","606624","606620","606618","606622","606619","606625"],"item_10005_date_7":{"attribute_name":"発表年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2005-07-27","subitem_date_issued_type":"Issued"}]},"item_10005_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"MRI画像では、腫瘍は周囲軟部組織とのコントラストが弱いため、腫瘍の検出を行うには相当の熟練が要求される。そこで、複数のMRI画像間の相関関係を客観的・自動的に構築し、腫瘍抽出を支援できるシステムができれば非常に有用である。骨軟部腫瘍症例に対し撮影された3種類（Gd造影、T1強調、T2強調）のMRI画像の画素値から自己組織化マップ（Self-Organizing Maps:SOM）の学習を行い、3種類の画像の相関に従って分布したマップを作成する。このマップに対してクラスタリングを行い、あらかじめ決められた数のクラスタに分類し、その結果を元画像に反映させることによってクラスタリング画像を作成して腫瘍の抽出を行った。本手法を用いることにより、腫瘍部位をT1の値が低く、T2とGdの値が高いクラスタとして分類することができた。今後は多くの症例に対して本手法を適用し、有効性を検証する必要がある。","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":"第24回日本医用画像工学会大会","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":"細田, 順一"}],"nameIdentifiers":[{"nameIdentifier":"606615","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"上村, 幸司"}],"nameIdentifiers":[{"nameIdentifier":"606616","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"小畠, 隆行"}],"nameIdentifiers":[{"nameIdentifier":"606617","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"生駒, 洋子"}],"nameIdentifiers":[{"nameIdentifier":"606618","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"安藤, 裕"}],"nameIdentifiers":[{"nameIdentifier":"606619","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"その他"}],"nameIdentifiers":[{"nameIdentifier":"606620","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"細田 順一","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"606621","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"上村 幸司","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"606622","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"小畠 隆行","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"606623","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"生駒 洋子","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"606624","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"安藤 裕","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"606625","nameIdentifierScheme":"WEKO"}]}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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":"自己組織化マップを用いた複数MRI画像からの腫瘍自動抽出法の開発","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"自己組織化マップを用いた複数MRI画像からの腫瘍自動抽出法の開発"}]},"item_type_id":"10005","owner":"1","path":["29"],"pubdate":{"attribute_name":"公開日","attribute_value":"2006-01-24"},"publish_date":"2006-01-24","publish_status":"0","recid":"61282","relation_version_is_last":true,"title":["自己組織化マップを用いた複数MRI画像からの腫瘍自動抽出法の開発"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-15T21:44:12.736795+00:00"}