{"created":"2023-05-15T14:43:57.914630+00:00","id":60125,"links":{},"metadata":{"_buckets":{"deposit":"9aa90daf-a479-40cd-938a-843129108c6f"},"_deposit":{"created_by":1,"id":"60125","owners":[1],"pid":{"revision_id":0,"type":"depid","value":"60125"},"status":"published"},"_oai":{"id":"oai:repo.qst.go.jp:00060125","sets":["10:29"]},"author_link":["597830","597824","597829","597834","597827","597831","597832","597833","597826","597825","597823","597828"],"item_10005_date_7":{"attribute_name":"発表年月日","attribute_value_mlt":[{"subitem_date_issued_datetime":"2003-10-29","subitem_date_issued_type":"Issued"}]},"item_10005_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":" 自己組織化マップ(SOM: Self-Organizing Maps)は,多次元の情報をもつデータを二次元のマップに表すことが可能である.\n本研究では複数種類の脳PET機能画像を対象とし,自己組織化マップを用いたクラスタリング手法により,機能の相関にしたがって分類された脳画像を作成した.また,各疾患の特徴的な機能の相関を示す部位が他の部位とは異なるクラスタとして客観的,自動的に分類されるよう,クラスタリング手法,クラスタ数の決定法などの検討を行った．さらに,階層的凝集型クラスタリングやK-means法など他の手法を用いてクラスタリングを行い,その分類結果との比較を行った.\n　本手法を側頭葉てんかん例に適用したところ,てんかんの焦点を正常部位と違うクラスタとして分類することが出来た.しかし,他の手法に比べて計算時間が長い等の問題があり,さらに方法を検討していく必要がある.\n","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43回日本核医学会総会","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":"大橋, 信一郎"}],"nameIdentifiers":[{"nameIdentifier":"597823","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"外山, 比南子"}],"nameIdentifiers":[{"nameIdentifier":"597824","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"上村, 幸司"}],"nameIdentifiers":[{"nameIdentifier":"597825","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"三品, 雅洋"}],"nameIdentifiers":[{"nameIdentifier":"597826","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"成相, 直"}],"nameIdentifiers":[{"nameIdentifier":"597827","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"石井, 賢二"}],"nameIdentifiers":[{"nameIdentifier":"597828","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"内山, 明彦"}],"nameIdentifiers":[{"nameIdentifier":"597829","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"大橋 信一郎","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"597830","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"外山 比南子","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"597831","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"上村 幸司","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"597832","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"成相 直","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"597833","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"石井 賢二","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"597834","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脳機能相関自動抽出法の検討-脳PET画像への応用-","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脳機能相関自動抽出法の検討-脳PET画像への応用-"}]},"item_type_id":"10005","owner":"1","path":["29"],"pubdate":{"attribute_name":"公開日","attribute_value":"2003-11-13"},"publish_date":"2003-11-13","publish_status":"0","recid":"60125","relation_version_is_last":true,"title":["自己組織化マップを用いた複数脳機能相関自動抽出法の検討-脳PET画像への応用-"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-05-15T21:57:13.764304+00:00"}