{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T20:46:28Z","timestamp":1792010788084,"version":"4.4.0"},"reference-count":27,"publisher":"Elsevier BV","issue":"12","license":[{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12326619"],"award-info":[{"award-number":["12326619"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017691","name":"Guangxi Key Research and Development Program","doi-asserted-by":"publisher","award":["AB23026042"],"award-info":[{"award-number":["AB23026042"]}],"id":[{"id":"10.13039\/501100017691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004607","name":"Natural Science Foundation of Guangxi Province","doi-asserted-by":"publisher","award":["2025GXNSFAA069471"],"award-info":[{"award-number":["2025GXNSFAA069471"]}],"id":[{"id":"10.13039\/501100004607","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["clinicalkey.com","clinicalkey.com.au","clinicalkey.es","clinicalkey.fr","clinicalkey.jp","umbjournal.org","elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Ultrasound in Medicine &amp; Biology"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1016\/j.ultrasmedbio.2026.08.015","type":"journal-article","created":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T11:25:33Z","timestamp":1789212333000},"page":"2807-2816","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning-based Intelligent Diagnosis of Congenital Uterine Anomalies in 3-D Ultrasound"],"prefix":"10.1016","volume":"52","author":[{"given":"Yueyue","family":"Xu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhao","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaxiao","family":"Deng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanji","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajia","family":"Qu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shiying","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaomei","family":"Tang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haining","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chengcai","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyi","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dong","family":"Ni","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyu","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0001","doi-asserted-by":"crossref","first-page":"369","DOI":"10.1097\/AOG.0000000000005469","article-title":"M\u00fcllerian anomalies: presentation, diagnosis, and counseling","volume":"143","author":"Bortoletto","year":"2024","journal-title":"Obstet Gynecol"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0002","doi-asserted-by":"crossref","first-page":"536","DOI":"10.1016\/j.jpag.2022.04.007","article-title":"Diagnosis and management of Mullerian anomalies across differing resource settings: worldwide adaptations","volume":"35","author":"Dietrich","year":"2022","journal-title":"J Pediatr Adolesc Gynecol"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0006","article-title":"A study of Mullerian anomalies in pregnancy: case series in a tertiary care centre","volume":"14","author":"Abhinaya","year":"2024","journal-title":"Int J Med Public Health"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0007","doi-asserted-by":"crossref","first-page":"944","DOI":"10.1016\/S0015-0282(16)59942-7","article-title":"The American Fertility Society classification of adnexal adhesions, distal tubal occlusion secondary to tubal ligation, tubal pregnancies, Mullerian anomalies and intrauterine adhesions","volume":"49","year":"1988","journal-title":"Fertil Steril"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0003","doi-asserted-by":"crossref","first-page":"761","DOI":"10.1093\/humupd\/dmr028","article-title":"The prevalence of congenital uterine anomalies in unselected and high-risk populations: a systematic review","volume":"17","author":"Chan","year":"2011","journal-title":"Hum Reprod Update"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0004","doi-asserted-by":"crossref","first-page":"366","DOI":"10.1002\/uog.23108","article-title":"Definition, prevalence, clinical relevance and treatment of T-shaped uterus: systematic review","volume":"57","author":"Coelho Neto","year":"2021","journal-title":"Ultrasound Obstet Gynecol"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0005","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1016\/j.rbmo.2021.06.003","article-title":"Prevalence of T-shaped uterus among fertile women based on ESHRE\/ESGE and Congenital Uterine Malformation by Experts (CUME) criteria","volume":"43","author":"Seyhan","year":"2021","journal-title":"Reprod Biomed Online"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0010","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.tjog.2020.01.003","article-title":"Diagnosis and treatment of M\u00fcllerian malformations","volume":"59","author":"de Passos","year":"2020","journal-title":"Taiwan J Obstet Gynecol"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0011","doi-asserted-by":"crossref","first-page":"408","DOI":"10.1016\/j.fertnstert.2019.07.005","article-title":"Reproductive surgery for M\u00fcllerian anomalies: a review of progress in the last decade","volume":"112","author":"Ludwin","year":"2019","journal-title":"Fertil Steril"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0008","series-title":"Paper presented at: International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"553","article-title":"Searching collaborative agents for multi-plane localization in 3D ultrasound","author":"Huang","year":"2020"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0009","article-title":"Artificial intelligence for detecting fetal orofacial clefts and advancing medical education","author":"Zhang","year":"2026","journal-title":"Nature Communications"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0012","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1146\/annurev-bioeng-071516-044442","article-title":"Deep learning in medical image analysis","volume":"19","author":"Shen","year":"2017","journal-title":"Annu Rev Biomed Eng"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0019","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1049\/cit2.12356","article-title":"Deep learning on medical image analysis","volume":"10","author":"Wang","year":"2025","journal-title":"CAAI Trans Intell Technol"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.103061","article-title":"Segment anything model for medical images?","volume":"92","author":"Huang","year":"2024","journal-title":"Med Image Anal"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0014","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2026.104201","article-title":"FAA-Net: fetal abdominal anomaly diagnosis in prenatal ultrasound via LLM-enhanced multi-instance learning","author":"Liang","year":"2026","journal-title":"Med Image Anal"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0015","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2024.107249","article-title":"Enhancing fetal ultrasound image quality assessment with multi-scale fusion and clustering-based optimization","volume":"102","author":"Chen","year":"2025","journal-title":"Biomed Signal Process Control"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0016","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2025.103552","article-title":"Flip learning: weakly supervised erase to segment nodules in breast ultrasound","volume":"102","author":"Huang","year":"2025","journal-title":"Med Image Anal"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0025","doi-asserted-by":"crossref","first-page":"1616","DOI":"10.1016\/j.ultrasmedbio.2023.03.013","article-title":"Real-time automatic assisted detection of uterine fibroid in ultrasound images using a deep learning detector","volume":"49","author":"Yang","year":"2023","journal-title":"Ultrasound Med Biol"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0026","series-title":"Paper presented at: International Conference on Computational Science","first-page":"50","article-title":"Classification of uterine fibroids in ultrasound images using deep learning model","author":"Dilna","year":"2022"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0020","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2024.108794","article-title":"Automatic segmentation and alignment of uterine shapes from 3D ultrasound data","volume":"178","author":"Bone\u0161","year":"2024","journal-title":"Comput Biol Med"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0021","doi-asserted-by":"crossref","first-page":"1950","DOI":"10.1109\/TMI.2021.3069663","article-title":"Agent with warm start and adaptive dynamic termination for plane localization in 3D ultrasound","volume":"40","author":"Yang","year":"2021","journal-title":"IEEE Trans Med Imaging"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0022","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2021.102119","article-title":"Searching collaborative agents for multi-plane localization in 3D ultrasound","volume":"72","author":"Yang","year":"2021","journal-title":"Med Image Anal"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0023","series-title":"Paper presented at: International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"300","article-title":"Agent with tangent-based formulation and anatomical perception for standard plane localization in 3D ultrasound","author":"Zou","year":"2022"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0018","series-title":"3D Ultrasound.","first-page":"239","article-title":"Localizing standard plane in 3D fetal ultrasound","author":"Huang","year":"2023"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.cmpb.2025.108619","article-title":"Standard plane localization using denoising diffusion model with multi-scale guidance","author":"Dou","year":"2025","journal-title":"Comput Methods Programs Biomed"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0027","doi-asserted-by":"crossref","first-page":"1259","DOI":"10.1038\/s41467-021-21466-z","article-title":"Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images","volume":"12","author":"Zhou","year":"2021","journal-title":"Nat Commun"},{"key":"10.1016\/j.ultrasmedbio.2026.08.015_bib0017","series-title":"Paper presented at: International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"650","article-title":"Uncertainty-aware diffusion and reinforcement learning for joint plane localization and anomaly diagnosis in 3D ultrasound","author":"Huang","year":"2025"}],"container-title":["Ultrasound in Medicine &amp; Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S030156292600339X?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S030156292600339X?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T20:05:19Z","timestamp":1792008319000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S030156292600339X"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":27,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2026,12]]}},"alternative-id":["S030156292600339X"],"URL":"https:\/\/doi.org\/10.1016\/j.ultrasmedbio.2026.08.015","relation":{},"ISSN":["0301-5629"],"issn-type":[{"value":"0301-5629","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Deep Learning-based Intelligent Diagnosis of Congenital Uterine Anomalies in 3-D Ultrasound","name":"articletitle","label":"Article Title"},{"value":"Ultrasound in Medicine & Biology","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.ultrasmedbio.2026.08.015","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}