{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00067022","sets":["1164:5352:5656:5934"]},"path":["5934"],"owner":"10","recid":"67022","title":["ベイズアプローチに基づいた断層画像の再構成"],"pubdate":{"attribute_name":"公開日","attribute_value":"2009-12-10"},"_buckets":{"deposit":"31a3d6fe-ccf4-4268-8a71-9702f00cd32e"},"_deposit":{"id":"67022","pid":{"type":"depid","value":"67022","revision_id":0},"owners":[10],"status":"published","created_by":10},"item_title":"ベイズアプローチに基づいた断層画像の再構成","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ベイズアプローチに基づいた断層画像の再構成"},{"subitem_title":"Reconstruction of tomographic image based on Bayes approach","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2009-12-10","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"電気通信大学大学院電気通信学研究科"},{"subitem_text_value":"電気通信大学電気通信学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Electro-Communications, The University of Electro-Communications","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Electro-Communications, The University of Electro-Communications","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/67022/files/IPSJ-BIO09019036.pdf"},"date":[{"dateType":"Available","dateValue":"2011-12-10"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-BIO09019036.pdf","filesize":[{"value":"436.0 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"41"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"1030aedd-90e3-472d-803a-e359dad300d7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2009 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山本, 翔"},{"creatorName":"庄野, 逸"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Sho, Yamamoto","creatorNameLang":"en"},{"creatorName":"Hayaru, Shouno","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12055912","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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"観測データから画像を再構成する技術は，様々な分野で非破壊検査の手法として応用されてきている．このうち信頼性の高い観測データが得られる場合では，最尤推定法に基づく手法が有効であるとされ，医療分野では ML-EM 法といった手法が用いられるようになっている．しかし観測データが低品質な場合，信号がノイズに埋もれてしまい，うまく再構成できない場合がある．ノイズに埋もれたデータからでも高画質に画像を再構成する方法として，ベイズアプローチを用いた MAP-EM 法が注目されている．本研究では ML-EM 法，MAP-EM 法それぞれの手法で画像再構成の計算機シミュレーションを行い，また MAP-EM 法についての改善点について検討した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"The technology to reconstruct an image from observation data has been applied as technique of nondestructive inspection in various fields. When we could get reliable observation data, method based on Maximum likelihood estimation is effective, and ML-EM method comes to be used in medical field. However, when observation data were low quality, A signal is buried among noises, and there is the case that I cannot reconstruct well. MAP-EM method which used idea based on Bayes approach is interested because we may reconstruct high quality image from such data. We simulate reconstruction method ML-EM and MAP-EM and consider improvement of MAP-EM in this paper.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告バイオ情報学（BIO）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2009-12-10","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"36","bibliographicVolumeNumber":"2009-BIO-19"}]},"relation_version_is_last":true,"weko_creator_id":"10"},"id":67022,"updated":"2025-01-22T00:46:35.920008+00:00","links":{},"created":"2025-01-18T23:27:37.623145+00:00"}