{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,25]],"date-time":"2026-09-25T22:41:43Z","timestamp":1790376103401,"version":"4.1.0"},"reference-count":26,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T00:00:00Z","timestamp":1722988800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T00:00:00Z","timestamp":1722988800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"crossref","award":["No.3332021013"],"award-info":[{"award-number":["No.3332021013"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"crossref"}]},{"name":"National High Level Hospital Clinical Research Funding","award":["2022-PUMCH-A-120"],"award-info":[{"award-number":["2022-PUMCH-A-120"]}]},{"name":"CAMS Innovation Fund for Medical Sciences","award":["No. 2022-I2M-C&T-A-005"],"award-info":[{"award-number":["No. 2022-I2M-C&T-A-005"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Global Spine Journal"],"published-print":{"date-parts":[[2025,5]]},"abstract":"<jats:sec>\n                    <jats:title>Study Design<\/jats:title>\n                    <jats:p>Cross-sectional study.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Imaging classification of adolescent idiopathic scoliosis (AIS) is directly related to the surgical strategy, but the artificial classification is complex and depends on doctors\u2019 experience. This study investigated deep learning-based automated classification methods (DL group) for AIS and validated the consistency of machine classification and manual classification (M group).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A total of 506 cases (81 males and 425 females) and 1812 AIS full spine images in the anteroposterior (AP), lateral (LAT), left bending (LB) and right bending (RB) positions were retrospectively used for training. The mean age was 13.6 \u00b1 1.8. The mean maximum Cobb angle was 46.8 \u00b1 12.0. U-Net semantic segmentation neural network technology and deep learning methods were used to automatically segment and establish the alignment relationship between multiple views of the spine, and to extract spinal features such as the Cobb angle. The type of each test case was automatically calculated according to Lenke\u2019s rule. An additional 107 cases of adolescent idiopathic scoliosis imaging were prospectively used for testing. The consistency of the DL group and M group was compared.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Automatic vertebral body segmentation and recognition, multi-view alignment of the spine and automatic Cobb angle measurement were implemented. Compare to the M group, the consistency of the DL group was significantly higher in 3 aspects: type of lateral convexity (0.989 vs 0.566), lumbar curvature modifier (0.932 vs 0.738), and sagittal plane modifier (0.987 vs 0.522).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Deep learning enables automated Cobb angle measurement and automated Lenke classification of idiopathic scoliosis whole spine radiographs with higher consistency than manual measurement classification.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/21925682241270036","type":"journal-article","created":{"date-parts":[[2024,8,7]],"date-time":"2024-08-07T08:28:32Z","timestamp":1723019312000},"page":"1924-1931","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":5,"title":["Artificial Intelligence Measurement of Preoperative Radiographs in Adolescent Idiopathic Scoliosis Based on Multiple-View Semantic Segmentation"],"prefix":"10.1177","volume":"15","author":[{"given":"Yulei","family":"Dong","sequence":"first","affiliation":[{"name":"Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6796-0637","authenticated-orcid":false,"given":"Jiahao","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shanqi","family":"Huang","sequence":"additional","affiliation":[{"name":"Beijing Sanyuanju Technology Co., Ltd., Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ling","family":"Wu","sequence":"additional","affiliation":[{"name":"Beijing Sanyuanju Technology Co., Ltd., Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hong","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9025-2014","authenticated-orcid":false,"given":"Yu","family":"Zhao","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China"},{"name":"State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2024,8,7]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2017.11669"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jot.2020.10.014"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.spinee.2022.03.016"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1097\/00007632-200202150-00013"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1186\/1748-7161-1-2"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.2106\/00004623-200108000-00006"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-31486-3"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2018.07.008"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1097\/BRS.0b013e3182a0c7c3"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.2174\/0115734056278130231218073650"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10480-w"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/3796202"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.134.2.6986054"},{"key":"e_1_3_3_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/BF00223081"},{"key":"e_1_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1097\/01.BRS.0000067265.52473.C3"},{"key":"e_1_3_3_17_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3035253"},{"key":"e_1_3_3_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106231"},{"key":"e_1_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-018-1088-1"},{"key":"e_1_3_3_20_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-021-00526-2"},{"key":"e_1_3_3_21_2","doi-asserted-by":"crossref","unstructured":"Ronneberger O Fischer P Brox T. U-net: Convolutional Networks for Biomedical Image Segmentation. International Conference on Medical image computing and computer-assisted intervention; Cham 2015:234-241.","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/4259471"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-023-49923-3"},{"key":"e_1_3_3_24_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-007-9026-7"},{"key":"e_1_3_3_25_2","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/9083916"},{"key":"e_1_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1260\/2040-2295.6.2.145"},{"key":"e_1_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2018.05.005"}],"container-title":["Global Spine Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/21925682241270036","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/21925682241270036","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/21925682241270036","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T07:20:58Z","timestamp":1777447258000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/21925682241270036"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,7]]},"references-count":26,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,5]]}},"alternative-id":["10.1177\/21925682241270036"],"URL":"https:\/\/doi.org\/10.1177\/21925682241270036","relation":{},"ISSN":["2192-5682","2192-5690"],"issn-type":[{"value":"2192-5682","type":"print"},{"value":"2192-5690","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,7]]}}}