{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T06:01:57Z","timestamp":1781762517889,"version":"3.54.5"},"reference-count":32,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T00:00:00Z","timestamp":1776643200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100020595","name":"National Science and Technology Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100020595","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","ejradiology.com","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["European Journal of Radiology"],"published-print":{"date-parts":[[2026,7]]},"DOI":"10.1016\/j.ejrad.2026.112880","type":"journal-article","created":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T14:52:19Z","timestamp":1776523939000},"page":"112880","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity"],"prefix":"10.1016","volume":"200","author":[{"given":"Hiroki","family":"Katagiri","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gaku","family":"Koyano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junya","family":"Katayanagi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kazutoshi","family":"Takahashi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuto","family":"Takahashi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi-Ren","family":"Tsai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han-Wei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu-Shan","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey J.P.","family":"Tsai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8151-705X","authenticated-orcid":false,"given":"Tetsuya","family":"Jinno","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ejrad.2026.112880_b0005","doi-asserted-by":"crossref","DOI":"10.7326\/AITC201708010","article-title":"Osteoporosis","volume":"167","author":"Ensrud","year":"2017","journal-title":"Ann. Intern. Med."},{"key":"10.1016\/j.ejrad.2026.112880_b0010","doi-asserted-by":"crossref","DOI":"10.1177\/1759720X211028360","article-title":"Prognostic factors for 1-year functional outcome, quality of life, care demands, and mortality after surgery in Taiwanese geriatric patients with a hip fracture: A prospective cohort study","volume":"13","author":"Chen","year":"2021","journal-title":"Ther. Adv. Musculoskelet. Dis."},{"key":"10.1016\/j.ejrad.2026.112880_b0015","doi-asserted-by":"crossref","first-page":"102","DOI":"10.3390\/jpm12010102","article-title":"Prognostic factors for mortality, activity of daily living, and quality of life in taiwanese older patients within 1 year following hip fracture surgery","volume":"12","author":"Chiang","year":"2022","journal-title":"J. Pers. Med."},{"key":"10.1016\/j.ejrad.2026.112880_b0020","doi-asserted-by":"crossref","DOI":"10.1177\/21514593211044644","article-title":"Predictors of in-hospital mortality in older adults undergoing hip fracture surgery: a case\u2013control study","volume":"12","author":"Chiang","year":"2021","journal-title":"Geriatr. Orthop. Surg. Rehabil."},{"key":"10.1016\/j.ejrad.2026.112880_b0025","doi-asserted-by":"crossref","first-page":"1534","DOI":"10.3390\/biom10111534","article-title":"Deep learning for osteoporosis classification using hip radiographs and patient clinical covariates","volume":"10","author":"Yamamoto","year":"2020","journal-title":"Biomolecules"},{"key":"10.1016\/j.ejrad.2026.112880_b0030","doi-asserted-by":"crossref","first-page":"19997","DOI":"10.1038\/s41598-021-99549-6","article-title":"Prediction of osteoporosis from simple hip radiography using deep learning algorithm","volume":"11","author":"Jang","year":"2021","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ejrad.2026.112880_b0035","doi-asserted-by":"crossref","DOI":"10.1177\/1759720X241237872","article-title":"Automated osteoporosis classification and T-score prediction using hip radiographs via deep learning algorithm","volume":"16","author":"Chen","year":"2024","journal-title":"Ther. Adv. Musculoskelet. Dis."},{"key":"10.1016\/j.ejrad.2026.112880_b0040","article-title":"Body mass index and self-rated health in East Asian countries: Comparison among South Korea","volume":"12","author":"Noh","year":"2017","journal-title":"China, Japan, and Taiwan, PLoS One."},{"key":"10.1016\/j.ejrad.2026.112880_b0045","doi-asserted-by":"crossref","first-page":"296","DOI":"10.6009\/jjrt.2024-1415","article-title":"Effect of gonadal protection on image quality in frontal hip radiography","volume":"80","author":"Ito","year":"2024","journal-title":"Nihon Hoshasen Gijutsu Gakkai Zasshi."},{"key":"10.1016\/j.ejrad.2026.112880_b0050","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1097\/RTI.0000000000000138","article-title":"Low dose computed tomography screening in Japan","volume":"30","author":"Nawa","year":"2015","journal-title":"J. Thorac. Imaging"},{"key":"10.1016\/j.ejrad.2026.112880_b0055","first-page":"267","volume":"12","year":"2024","journal-title":"Image Quality, Radiation Dose, and Patient Comfort Associated with Wireless Sensors in Digital Radiography: A Systematic Review"},{"key":"10.1016\/j.ejrad.2026.112880_b0060","doi-asserted-by":"crossref","first-page":"1328","DOI":"10.3390\/diagnostics14131328","article-title":"Exploring the impact of noise and image quality on deep learning performance in DXA images","volume":"14","author":"Hussain","year":"2024","journal-title":"Diagnostics (basel)."},{"key":"10.1016\/j.ejrad.2026.112880_b0065","unstructured":"International Society for Clinical Densitometry, Official positions 2023. https:\/\/iscd.org\/official-positions-2023\/ (accessed 12 December 2025)."},{"key":"10.1016\/j.ejrad.2026.112880_b0070","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1007\/s00259-024-06912-6","article-title":"Updated practice guideline for dual-energy X-ray absorptiometry (DXA)","volume":"52","author":"Slart","year":"2025","journal-title":"Eur. J. Nucl. Med. Mol. Imaging"},{"key":"10.1016\/j.ejrad.2026.112880_b0075","first-page":"39","article-title":"Use of dual-energy X-ray absorptiometry (DXA) for diagnosis and fracture risk assessment","volume":"104","author":"Dimai","year":"2017","journal-title":"WHO-Criteria, T- and Z-Score, and Reference Databases, Bone."},{"key":"10.1016\/j.ejrad.2026.112880_b0080","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1093\/ije\/dyu084","article-title":"JPOS Study Group, Cohort profile: The Japanese population-based osteoporosis (JPOS) cohort study","volume":"44","author":"Iki","year":"2015","journal-title":"Int. J. Epidemiol."},{"key":"10.1016\/j.ejrad.2026.112880_b0085","doi-asserted-by":"crossref","unstructured":"C.Y. Wang, I.H. Yeh, L.H. Mark, YOLOv9: learning what you want to learn using programmable gradient information, in: A. Leonardis (Ed.), Proceedings of the European Conference on Computer Vision (ECCV 2024), Springer, Berlin, 2025, pp. 1\u201321. Doi: 10.1007\/978-3-031-72751-1_1.","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"10.1016\/j.ejrad.2026.112880_b0090","doi-asserted-by":"crossref","first-page":"199","DOI":"10.46604\/aiti.2021.6939","article-title":"Tea verification using triplet loss convolutional network","volume":"6","author":"Chen","year":"2021","journal-title":"Adv. Technol. Innov."},{"key":"10.1016\/j.ejrad.2026.112880_b0095","series-title":"In: 2017 IEEE International Conference on Computer Vision (ICCV)","first-page":"618","article-title":"Grad-CAM: visual explanations from deep networks via gradient-based localization","author":"Selvaraju","year":"2017"},{"key":"10.1016\/j.ejrad.2026.112880_b0100","doi-asserted-by":"crossref","first-page":"991","DOI":"10.1186\/s12891-024-08120-7","article-title":"Diagnostic accuracy of deep learning in prediction of osteoporosis: a systematic review and meta-analysis","volume":"25","author":"Amani","year":"2024","journal-title":"BMC Musculoskelet. Disord."},{"key":"10.1016\/j.ejrad.2026.112880_b0105","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12880-025-01626-z","article-title":"Deep learning-based evaluation of panoramic radiographs for osteoporosis screening: a systematic review and meta-analysis","volume":"25","author":"Tarighatnia","year":"2025","journal-title":"BMC Med. Imaging"},{"key":"10.1016\/j.ejrad.2026.112880_b0110","doi-asserted-by":"crossref","first-page":"1450","DOI":"10.3390\/diagnostics15121450","article-title":"Standardisation and optimisation of chest and pelvis X-ray imaging protocols across multiple radiography systems in a radiology department","volume":"15","author":"Abdi","year":"2025","journal-title":"Diagnostics"},{"key":"10.1016\/j.ejrad.2026.112880_b0115","doi-asserted-by":"crossref","first-page":"633","DOI":"10.1186\/s12891-020-03646-y","article-title":"Bone mineral density reference values in Singaporean adults and comparisons for osteoporosis establishment \u2013 The Yishun Study","volume":"21","author":"Chen","year":"2020","journal-title":"BMC Musculoskelet. Disord."},{"key":"10.1016\/j.ejrad.2026.112880_b0120","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.afos.2020.11.005","article-title":"Different reference ranges affect the prevalence of osteoporosis and osteopenia in an urban adult Malaysian population","volume":"6","author":"Yeap","year":"2020","journal-title":"Osteoporos. Sarcopenia."},{"key":"10.1016\/j.ejrad.2026.112880_b0125","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1007\/s00774-015-0676-0","article-title":"Different reference BMDs affect the prevalence of osteoporosis","volume":"34","author":"Jung","year":"2016","journal-title":"J. Bone Miner. Metab."},{"key":"10.1016\/j.ejrad.2026.112880_b0130","first-page":"579","article-title":"Influence of different reference databases on categorization of bone mineral density: a study on rural postmenopausal women from Southern India, Indian","volume":"22","author":"Paul","year":"2018","journal-title":"J. Endocrinol. Metab."},{"key":"10.1016\/j.ejrad.2026.112880_b0135","doi-asserted-by":"crossref","first-page":"25206","DOI":"10.1038\/srep25206","article-title":"Prevalence of osteoporosis and low bone mass in older chinese population based on bone mineral density at multiple skeletal sites","volume":"6","author":"Lu","year":"2016","journal-title":"Sci. Rep."},{"key":"10.1016\/j.ejrad.2026.112880_b0140","doi-asserted-by":"crossref","first-page":"7650","DOI":"10.21037\/qims-23-1090","article-title":"Conversion of measured bone mineral density T scores of Chinese women to equivalent Caucasian women\u2019s T score values","volume":"13","author":"Xiao","year":"2023","journal-title":"Quant. Imaging Med. Surg."},{"key":"10.1016\/j.ejrad.2026.112880_b0145","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1007\/s00256-023-04423-3","article-title":"East Asians\u2019 T-scores for the diagnosis of osteoporosis should be calculated using ethnicity- and gender-specific BMD reference ranges: justifications","volume":"53","author":"W\u00e1ng","year":"2024","journal-title":"Skeletal Radiol."},{"key":"10.1016\/j.ejrad.2026.112880_b0150","doi-asserted-by":"crossref","first-page":"2066","DOI":"10.21037\/qims-2020-16","article-title":"Chinese expert consensus on the diagnosis of osteoporosis by imaging and bone mineral density","volume":"10","author":"Cheng","year":"2020","journal-title":"Quant. Imaging Med. Surg."},{"issue":"2024","key":"10.1016\/j.ejrad.2026.112880_b0155","first-page":"609","article-title":"Revision of the World Health Organization T-score definition of osteoporosis for use in older East Asian women and men to reconcile it with their lifetime risk of fragility fracture","volume":"53","author":"W\u00e1ng","year":"1994","journal-title":"Skeletal Radiol."},{"key":"10.1016\/j.ejrad.2026.112880_b0160","doi-asserted-by":"crossref","first-page":"327","DOI":"10.1265\/jjh.61.327","article-title":"Relationship of changes in radius bone mineral density during seven years in working women around thirty years old with lifestyle, body measurement data and laboratory data","volume":"61","author":"Komiya","year":"2006","journal-title":"Nihon Eiseigaku Zasshi."}],"container-title":["European Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0720048X26002287?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0720048X26002287?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,30]],"date-time":"2026-05-30T00:42:37Z","timestamp":1780101757000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0720048X26002287"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":32,"alternative-id":["S0720048X26002287"],"URL":"https:\/\/doi.org\/10.1016\/j.ejrad.2026.112880","relation":{},"ISSN":["0720-048X"],"issn-type":[{"value":"0720-048X","type":"print"}],"subject":[],"published":{"date-parts":[[2026,7]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep-learning framework for osteoporosis screening on low-dose X-rays: Addressing image quality variability and cross-ethnic database Heterogeneity","name":"articletitle","label":"Article Title"},{"value":"European Journal of Radiology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ejrad.2026.112880","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier B.V.","name":"copyright","label":"Copyright"}],"article-number":"112880"}}