{"created":"2024-08-28T02:26:50.452841+00:00","id":2001484,"links":{},"metadata":{"_buckets":{"deposit":"edb1b9d6-6bd8-466c-9b53-f0c0da9ebbd9"},"_deposit":{"created_by":10,"id":"2001484","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"2001484"},"status":"published"},"_oai":{"id":"oai:repository.lib.tottori-u.ac.jp:02001484","sets":["1:9","2:12","23:34:1710471377862:1725515186456"]},"author_link":["326"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2024-05-28","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicNumberOfPages":"8","bibliographicPageEnd":"107","bibliographicPageStart":"100","bibliographicVolumeNumber":"67","bibliographic_titles":[{"bibliographic_title":"Yonago Acta Medica","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Background: We assessed and compared the image quality of normal and pathologic structures as well as the image noise in chest computed tomography images using “adaptive statistical iterative reconstruction-V” (ASiR-V) or deep learning reconstruction “TrueFidelity”. Methods: Forty consecutive patients with suspected lung disease were evaluated. The 1.25-mm axial images and 2.0-mm coronal multiplanar images were reconstructed under the following three conditions: (i) ASiR-V, lung kernel with 60% of ASiR-V; (ii) TF-M, standard kernel, image filter (Lung) with TrueFidelity at medium strength; and (iii) TF-H, standard kernel, image filter (Lung) with TrueFidelity at high strength. Two radiologists (readers) independently evaluated the image quality of anatomic structures using a scale ranging from 1 (best) to 5 (worst). In addition, readers ranked their image preference. Objective image noise was measured using a circular region of interest in the lung parenchyma. Subjective image quality scores, total scores for normal and abnormal structures, and lesion detection were compared using Wilcoxon’s signed-rank test. Objective image quality was compared using Student’s paired t-test and Wilcoxon’s signed-rank test. The Bonferroni correction was applied to the P value, and significance was assumed only for values of P < 0.016. Results: Both readers rated TF-M and TF-H images significantly better than ASiR-V images in terms of visualization of the centrilobular region in axial images. The preference score of TF-M and TF-H images for reader 1 were better than that of ASiR-V images, and the preference score of TF-H images for reader 2 were significantly better than that of ASiR-V and TF-M images. TF-M images showed significantly lower objective image noise than ASiR-V or TF-H images. Conclusion: TrueFidelity showed better image quality, especially in the centrilobular region, than ASiR-V in subjective and objective evaluations. In addition, the image texture preference for TrueFidelity was better than that for ASiR-V.","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Tottori University Medical Press","subitem_publisher_language":"en"}]},"item_10001_relation_16":{"attribute_name":"情報源","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"Yonago Acta Medica. 2024, 67(2), 100-107."}]}]},"item_10001_relation_17":{"attribute_name":"関連サイト","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"https://www.lib.tottori-u.ac.jp/yam/yam/yam67-2/67-2contents.html"}],"subitem_relation_type_id":{"subitem_relation_type_id_text":"https://www.lib.tottori-u.ac.jp/yam/yam/yam67-2/67-2contents.html","subitem_relation_type_select":"URI"}},{"subitem_relation_name":[{"subitem_relation_name_text":"https://doi.org/10.33160/yam.2024.05.001"}],"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.33160/yam.2024.05.001","subitem_relation_type_select":"DOI"}}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"(C)2024 Tottori University Medical Press","subitem_rights_language":"en"}]},"item_10001_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA00892882","subitem_source_identifier_type":"NCID"}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"05135710","subitem_source_identifier_type":"PISSN"},{"subitem_source_identifier":"13468049","subitem_source_identifier_type":"EISSN"}]},"item_10001_text_33":{"attribute_name":"著者所属（英）","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Division of Radiology, Department of Multidisciplinary Internal Medicine, School of Medicine, Faculty of Medicine, Tottori University"},{"subitem_text_language":"en","subitem_text_value":"Division of Radiology, Department of Multidisciplinary Internal Medicine, School of Medicine, Faculty of Medicine, Tottori University"},{"subitem_text_language":"en","subitem_text_value":"Division of Radiology, Department of Multidisciplinary Internal Medicine, School of Medicine, Faculty of Medicine, Tottori University"},{"subitem_text_language":"en","subitem_text_value":"Division of Radiology, Department of Multidisciplinary Internal Medicine, School of Medicine, Faculty of Medicine, Tottori University"},{"subitem_text_language":"en","subitem_text_value":"Division of Clinical Radiology, School of Medicine, Faculty of Medicine, Tottori University"},{"subitem_text_language":"en","subitem_text_value":"Department of Data Science, The Institute of Statistical Mathematics"},{"subitem_text_language":"en","subitem_text_value":"Division of Radiology, Department of Multidisciplinary Internal Medicine, School of Medicine, Faculty of Medicine, Tottori University"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open 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":[{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"15101","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"鳥取大学","affiliationNameLang":"ja"},{"affiliationName":"Tottori University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"Yunaga,Hiroto","creatorNameLang":"en"}],"familyNames":[{"familyName":"Yunaga","familyNameLang":"en"}],"givenNames":[{"givenName":"Hiroto","givenNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"15101","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"鳥取大学","affiliationNameLang":"ja"},{"affiliationName":"Tottori University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"Miyoshi,Hidenao","creatorNameLang":"en"}],"familyNames":[{"familyName":"Miyoshi","familyNameLang":"en"}],"givenNames":[{"givenName":"Hidenao","givenNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"15101","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"鳥取大学","affiliationNameLang":"ja"},{"affiliationName":"Tottori University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"Ochiai,Ryoya","creatorNameLang":"en"}],"familyNames":[{"familyName":"Ochiai","familyNameLang":"en"}],"givenNames":[{"givenName":"Ryoya","givenNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"15101","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"鳥取大学","affiliationNameLang":"ja"},{"affiliationName":"Tottori University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"Gonda,Takuro","creatorNameLang":"en"}],"familyNames":[{"familyName":"Gonda","familyNameLang":"en"}],"givenNames":[{"givenName":"Takuro","givenNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"15101","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"鳥取大学","affiliationNameLang":"ja"},{"affiliationName":"Tottori University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"Sakoh,Toshio","creatorNameLang":"en"}],"familyNames":[{"familyName":"Sakoh","familyNameLang":"en"}],"givenNames":[{"givenName":"Toshio","givenNameLang":"en"}]},{"creatorNames":[{"creatorName":"Noma,Hisashi","creatorNameLang":"en"}],"familyNames":[{"familyName":"Noma","familyNameLang":"en"}],"givenNames":[{"givenName":"Hisashi","givenNameLang":"en"}]},{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"15101","affiliationNameIdentifierScheme":"kakenhi"}],"affiliationNames":[{"affiliationName":"鳥取大学","affiliationNameLang":"ja"},{"affiliationName":"Tottori University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"藤井,進也","creatorNameLang":"ja"},{"creatorName":"Fujii,Shinya","creatorNameLang":"en"},{"creatorName":"フジイ,シンヤ","creatorNameLang":"ja-Kana"}],"familyNames":[{"familyName":"藤井","familyNameLang":"ja"},{"familyName":"Fujii","familyNameLang":"en"},{"familyName":"フジイ","familyNameLang":"ja-Kana"}],"givenNames":[{"givenName":"進也","givenNameLang":"ja"},{"givenName":"Shinya","givenNameLang":"en"},{"givenName":"シンヤ","givenNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"326","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"100000415","nameIdentifierScheme":"研究者総覧鳥取大学","nameIdentifierURI":"http://researchers.adm.tottori-u.ac.jp/html/100000415ja.html"},{"nameIdentifier":"10379638","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=10379638"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2024-05-28"}],"displaytype":"detail","fileDate":[{"fileDateType":"Issued","fileDateValue":"2024-05-28"}],"filename":"yam67(2)_100.pdf","filesize":[{"value":"2.4 MB"}],"format":"application/pdf","licensefree":"(C)2024 Tottori University Medical Press","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"yam66(4)_100.pdf","objectType":"fulltext","url":"https://repository.lib.tottori-u.ac.jp/record/2001484/files/yam67(2)_100.pdf"},"version_id":"da7f265d-02e9-4aac-a455-583780a7a4bc"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"deep learning","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"diagnostic imaging","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"image processing","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"computer-assisted","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"lung","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"multidetector computed tomography","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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":"Image Quality and Lesion Detection of Multiplanar Reconstruction Images Using Deep Learning: Comparison with Hybrid Iterative Reconstruction","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Image Quality and Lesion Detection of Multiplanar Reconstruction Images Using Deep Learning: Comparison with Hybrid Iterative Reconstruction","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"10","path":["12","9","1725515186456"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2024-08-28"},"publish_date":"2024-08-28","publish_status":"0","recid":"2001484","relation_version_is_last":true,"title":["Image Quality and Lesion Detection of Multiplanar Reconstruction Images Using Deep Learning: Comparison with Hybrid Iterative Reconstruction"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2024-10-18T07:01:01.176514+00:00"}