{"created":"2021-03-01T06:29:14.855906+00:00","id":21564,"links":{},"metadata":{"_buckets":{"deposit":"47b7e3f0-89ef-410a-b70d-9fdcc36a01e3"},"_deposit":{"id":"21564","owners":[],"pid":{"revision_id":0,"type":"depid","value":"21564"},"status":"published"},"_oai":{"id":"oai:nagoya.repo.nii.ac.jp:00021564","sets":["312:313:314"]},"author_link":["63212","63213","63214","63215","63216","63217","63218","63219","63220","63221","63222","63223","63224","63225"],"item_10_alternative_title_19":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"A Study on Multiple Organ Segmentation from 3D CT Images Based on Normalization Method and Patient-Specific Probabilistic Map","subitem_alternative_title_language":"en"}]},"item_10_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2013-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"411","bibliographicPageEnd":"144","bibliographicPageStart":"139","bibliographicVolumeNumber":"112","bibliographic_titles":[{"bibliographic_title":"電子情報通信学会技術研究報告. MI, 医用画像","bibliographic_titleLang":"ja"}]}]},"item_10_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"3次元腹部CT像からの臓器領域の抽出においては、体格における患者間の個人差が大きく、各CT像上の臓器の大きさ・位置が大きく異なるため、CT像データベースを臓器抽出に利用する場合、各CT像データに対して体格の正規化を行う必要がある。本稿では、新たな体格正規化手法に基づいた個別尤度マップの構築およびそれを用いた腹部複数臓器領域の抽出手法を提案する。具体的には、まず抽出しやすい肺野領域と腎臓領域を粗抽出し、これらの領域情報に基づいて体格正規化を行う。その後、体格正規化したCT像データベースを用い、新しいCTデータごとに臓器存在尤度マップ(個別尤度マップ)を動的に構築し、臓器領域の粗抽出を行い、グラフカットにより精密抽出を行う腹部CT像100例を用いた実験を行い、肝臓、脾臓、膵臓、腎臓領域の抽出においてそれぞれ95.1%、91.4%、69.1%、90.1%の抽出精度が得られた。 ","subitem_description_language":"ja","subitem_description_type":"Abstract"},{"subitem_description":"Organ segmentation from 3D abdominal CT database is a difficult process due to the large differences among patients in organ size and location. It is necessary to normalize physical size for each CT data in the database if CT database is utilized for organ segmentation. In this paper, we propose a new normalization method on physical size. Also, we incorporate it into a patient-specific atlas based method for multi-organ segmentation. Firstly, we roughly extract lung and kidney areas to normalize the physical sizes of the CT images in database. We dynamically generate a patient-specific probabilistic atlas for each new target image by using the normalized CT database. We roughly segment the organ region based on the probabilistic atlas and refine it by using a graph-cuts method. Experimental results showed that our approach can segment the liver, the spleen, the pancreas, and the kidney correctly with Jaccard indices of 95.1%, 91.4%, 69.1%, and 90.1%, respectively.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"IEICE Technical Report;MI2012-89","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_10_identifier_60":{"attribute_name":"URI","attribute_value_mlt":[{"subitem_identifier_type":"URI","subitem_identifier_uri":"http://ci.nii.ac.jp/naid/110009727720/"},{"subitem_identifier_type":"HDL","subitem_identifier_uri":"http://hdl.handle.net/2237/23712"}]},"item_10_publisher_32":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"一般社団法人電子情報通信学会","subitem_publisher_language":"ja"}]},"item_10_relation_40":{"attribute_name":"シリーズ","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"IEICE Technical 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access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_abf2"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"チョ, 成文","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63212","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"小田, 昌宏","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63213","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"北坂, 孝幸","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63214","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"三澤, 一成","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63215","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"藤原, 道隆","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63216","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"林, 雄一郎","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63217","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"森, 健策","creatorNameLang":"ja"}],"nameIdentifiers":[{"nameIdentifier":"63218","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"CHU, Chengwen","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63219","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"ODA, Masahiro","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63220","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"KITASAKA, Takayuki","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63221","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"MISAWA, Kazunari","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63222","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"FUJIWARA, Michitaka","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63223","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"HAYASHI, Yuichiro","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63224","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"MORI, Kensaku","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"63225","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2018-02-21"}],"displaytype":"detail","filename":"110009727720.pdf","filesize":[{"value":"1.3 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"110009727720.pdf","objectType":"fulltext","url":"https://nagoya.repo.nii.ac.jp/record/21564/files/110009727720.pdf"},"version_id":"a5a898f8-e7b4-4ddd-87d6-96cf6f70b7f2"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"CT像","subitem_subject_scheme":"Other"},{"subitem_subject":"セグメンテーション","subitem_subject_scheme":"Other"},{"subitem_subject":"体格正規化","subitem_subject_scheme":"Other"},{"subitem_subject":"個別尤度マップ","subitem_subject_scheme":"Other"},{"subitem_subject":"CT image","subitem_subject_scheme":"Other"},{"subitem_subject":"segmentation","subitem_subject_scheme":"Other"},{"subitem_subject":"normalization of physical size","subitem_subject_scheme":"Other"},{"subitem_subject":"patient−specific probabilistic atlas","subitem_subject_scheme":"Other"}]},"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":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"体格正規化手法と個別尤度マップを用いた3次元腹部CT像からの複数臓器抽出手法に関する検討","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"体格正規化手法と個別尤度マップを用いた3次元腹部CT像からの複数臓器抽出手法に関する検討","subitem_title_language":"ja"}]},"item_type_id":"10","owner":"1","path":["314"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2016-03-03"},"publish_date":"2016-03-03","publish_status":"0","recid":"21564","relation_version_is_last":true,"title":["体格正規化手法と個別尤度マップを用いた3次元腹部CT像からの複数臓器抽出手法に関する検討"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2023-01-16T04:10:40.289492+00:00"}