{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T15:05:28Z","timestamp":1775315128960,"version":"3.50.1"},"reference-count":55,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,11,1]],"date-time":"2026-11-01T00:00:00Z","timestamp":1793491200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:00:00Z","timestamp":1774310400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100013076","name":"National Major Science and Technology Projects of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013076","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2026,11]]},"DOI":"10.1016\/j.patcog.2026.113515","type":"journal-article","created":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T07:32:34Z","timestamp":1774078354000},"page":"113515","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PA","title":["Boosting cross-domain semi-supervised medical image segmentation with internal and external regularizations"],"prefix":"10.1016","volume":"179","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5969-0478","authenticated-orcid":false,"given":"Rui","family":"Wang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3975-2483","authenticated-orcid":false,"given":"Fan","family":"Tang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8834-9646","authenticated-orcid":false,"given":"Feiyue","family":"Huang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8396-8815","authenticated-orcid":false,"given":"Shaoxin","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6399-3415","authenticated-orcid":false,"given":"Xinkun","family":"Xu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-9732-071X","authenticated-orcid":false,"given":"Yuchen","family":"Xu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8129-0060","authenticated-orcid":false,"given":"Lifeng","family":"Zhu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7399-7011","authenticated-orcid":false,"given":"Weiming","family":"Dong","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.113515_bib0001","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"509","article-title":"DeSAM: decoupled segment anything model for generalizable medical image segmentation","author":"Gao","year":"2024"},{"issue":"10","key":"10.1016\/j.patcog.2026.113515_bib0002","doi-asserted-by":"crossref","first-page":"8801","DOI":"10.1609\/aaai.v35i10.17066","article-title":"Semi-supervised medical image segmentation through dual-task consistency","volume":"35","author":"Luo","year":"2021","journal-title":"Proceedings of the AAAI Conference on Artificial Intelligence"},{"key":"10.1016\/j.patcog.2026.113515_bib0003","series-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2022","first-page":"34","article-title":"Exploring smoothness and class-separation for semi-supervised medical image segmentation","author":"Wu","year":"2022"},{"key":"10.1016\/j.patcog.2026.113515_bib0004","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.patrec.2025.04.014","article-title":"CycleMatch: cyclic pseudo-labeling distillation in semi-supervised medical image segmentation","volume":"193","author":"Wang","year":"2025","journal-title":"Pattern Recognit. Lett."},{"key":"10.1016\/j.patcog.2026.113515_bib0005","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"15651","article-title":"MCF: mutual correction framework for semi-supervised medical image segmentation","author":"Yongchao","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0006","series-title":"Medical Image Computing and Computer Assisted Intervention","first-page":"98","article-title":"Correlation-aware mutual learning for semi-supervised medical image segmentation","author":"Shengbo","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0007","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.111216","article-title":"Multi-consistency for semi-supervised medical image segmentation via diffusion models","volume":"161","author":"Chen","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113515_bib0008","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"151","article-title":"MaxStyle: adversarial style composition for robust medical image segmentation","author":"Chen","year":"2022"},{"key":"10.1016\/j.patcog.2026.113515_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112406","article-title":"Aegis: a domain generalization framework for medical image segmentation by mitigating feature misalignment","volume":"172","author":"Xu","year":"2026","journal-title":"Pattern Recognit."},{"issue":"4","key":"10.1016\/j.patcog.2026.113515_bib0010","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1109\/TMI.2022.3224067","article-title":"Causality-inspired single-source domain generalization for medical image segmentation","volume":"42","author":"Cheng","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.113515_bib0011","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112082","article-title":"A hybrid dual-augmentation constraint framework for single-source domain generalization in medical image segmentation","volume":"170","author":"Wang","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113515_bib0012","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.111416","article-title":"Generative feature style augmentation for domain generalization in medical image segmentation","volume":"162","author":"Huang","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113515_bib0013","series-title":"Medical Image Computing and Computer Assisted Intervention","first-page":"307","article-title":"Semi-supervised meta-learning with disentanglement for domain-generalised medical image segmentation","author":"Xiao","year":"2021"},{"key":"10.1016\/j.patcog.2026.113515_bib0014","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"11018","article-title":"Semi-supervised domain adaptation based on dual-level domain mixing for semantic segmentation","author":"Shuaijun","year":"2021"},{"key":"10.1016\/j.patcog.2026.113515_bib0015","series-title":"Medical Image Computing and Computer Assisted Intervention","first-page":"66","article-title":"ACT: semi-supervised domain-adaptive medical image segmentation with asymmetric co-training","author":"Xiaofeng","year":"2022"},{"issue":"4","key":"10.1016\/j.patcog.2026.113515_bib0016","doi-asserted-by":"crossref","DOI":"10.1145\/3501800","article-title":"Towards corruption-agnostic robust domain adaptation","volume":"18","author":"Xu","year":"2022","journal-title":"ACM Trans. Multimed. Comput. Commun. Appl."},{"key":"10.1016\/j.patcog.2026.113515_bib0017","series-title":"Proceedings of the IEEE\/CVF International Conference on Computer Vision","first-page":"4015","article-title":"Segment anything","author":"Kirillov","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0018","unstructured":"W. Junde, F. Rao, F. Huihui, L. Yuanpei, W. Zhaowei, X. Yanwu, J. Yueming, T. Arbel, Medical sam adapter: adapting segment anything model for medical image segmentation, arXiv: 2304.12620(2023)."},{"issue":"1","key":"10.1016\/j.patcog.2026.113515_bib0019","article-title":"Segment anything in medical images","volume":"15","author":"Ma","year":"2024","journal-title":"Nat. Commun."},{"key":"10.1016\/j.patcog.2026.113515_bib0020","series-title":"2024\u202fIEEE International Conference on Bioinformatics and Biomedicine (BIBM)","first-page":"3982","article-title":"SemiSAM: enhancing semi-supervised medical image segmentation via SAM-assisted consistency regularization","author":"Zhang","year":"2024"},{"key":"10.1016\/j.patcog.2026.113515_bib0021","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"11418","article-title":"PH-Net: semi-supervised breast lesion segmentation via patch-wise hardness","author":"Jiang","year":"2024"},{"key":"10.1016\/j.patcog.2026.113515_bib0022","series-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2020","first-page":"552","article-title":"Shape-aware semi-supervised 3D semantic segmentation for medical images","author":"Shuailin","year":"2020"},{"key":"10.1016\/j.patcog.2026.113515_bib0023","series-title":"Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2021","first-page":"318","article-title":"Efficient semi-supervised gross target volume of nasopharyngeal carcinoma segmentation via uncertainty rectified pyramid consistency","author":"Luo","year":"2021"},{"key":"10.1016\/j.patcog.2026.113515_bib0024","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112310","article-title":"Semi-supervised medical image segmentation via pseudo-labeling refinement and dual-adaptive adjustment schemes","volume":"171","author":"Zheng","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.113515_bib0025","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2025.112311","article-title":"Unsupervised cross-domain semantic segmentation on multi-modality ovarian tumor ultrasound data","volume":"171","author":"Lyu","year":"2026","journal-title":"Pattern Recognit."},{"issue":"8","key":"10.1016\/j.patcog.2026.113515_bib0026","doi-asserted-by":"crossref","first-page":"3172","DOI":"10.1007\/s11263-024-02028-4","article-title":"Domain generalization with small data","volume":"132","author":"Chen","year":"2024","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.patcog.2026.113515_bib0027","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"260","article-title":"Semi-supervised domain adaptive medical image segmentation through consistency regularized disentangled contrastive learning","author":"Basak","year":"2023"},{"issue":"7","key":"10.1016\/j.patcog.2026.113515_bib0028","doi-asserted-by":"crossref","first-page":"2693","DOI":"10.1109\/TMI.2024.3371987","article-title":"Learning robust shape regularization for generalizable medical image segmentation","volume":"43","author":"Chen","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"9","key":"10.1016\/j.patcog.2026.113515_bib0029","doi-asserted-by":"crossref","first-page":"3098","DOI":"10.1109\/TMI.2024.3387415","article-title":"FPL+: filtered pseudo label-based unsupervised cross-modality adaptation for 3D medical image segmentation","volume":"43","author":"Wu","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"8","key":"10.1016\/j.patcog.2026.113515_bib0030","doi-asserted-by":"crossref","first-page":"2936","DOI":"10.1109\/TMI.2024.3382624","article-title":"Towards accurate cardiac MRI segmentation with variational autoencoder-based unsupervised domain adaptation","volume":"43","author":"Cui","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.113515_bib0031","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"8300","article-title":"Semantic segmentation with generative models: semi-supervised learning and strong out-of-domain generalization","author":"Daiqing","year":"2021"},{"key":"10.1016\/j.patcog.2026.113515_bib0032","series-title":"International Conference on Learning Representations","article-title":"Domain generalization with MixStyle","author":"Zhou","year":"2021"},{"key":"10.1016\/j.patcog.2026.113515_bib0033","series-title":"Medical Image Computing and Computer Assisted Intervention","first-page":"89","article-title":"Treasure in distribution: a domain randomization based multi-source domain generalization for 2D medical image segmentation","author":"Ziyang","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0034","series-title":"Medical Imaging with Deep Learning, Short Paper Track","article-title":"SAM.MD: zero-shot medical image segmentation capabilities of the segment anything model","author":"Wald","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0035","unstructured":"S. He, R. Bao, J. Li, P.E. Grant, Y. Ou, Accuracy of Segment-Anything Model (SAM) in medical image segmentation tasks, (2023). 10.48550\/arXiv.2304.09324."},{"key":"10.1016\/j.patcog.2026.113515_bib0036","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2023.102918","article-title":"Segment anything model for medical image analysis: an experimental study","volume":"89","author":"Mazurowski","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.113515_bib0037","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"129","article-title":"Input augmentation with sam: boosting medical image segmentation with segmentation foundation model","author":"Zhang","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0038","series-title":"Proceedings of Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024","first-page":"24","article-title":"Beyond adapting SAM: towards end-to-end ultrasound image segmentation via auto prompting","volume":"LNCS 15008","author":"Lin","year":"2024"},{"key":"10.1016\/j.patcog.2026.113515_bib0039","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"437","article-title":"MBA-Net: SAM-driven bidirectional aggregation network for ovarian tumor segmentation","author":"Gao","year":"2024"},{"key":"10.1016\/j.patcog.2026.113515_bib0040","series-title":"Proceedings of Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024","first-page":"596","article-title":"CS3: cascade SAM for sperm segmentation","volume":"LNCS 15003","author":"Shi","year":"2024"},{"key":"10.1016\/j.patcog.2026.113515_bib0041","series-title":"Proceedings of the AAAI Conference on Artificial Intelligence","first-page":"2366","article-title":"Rethinking data augmentation for single-source domain generalization in medical image segmentation","author":"Zixian","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0042","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"11514","article-title":"Bidirectional copy-paste for semi-supervised medical image segmentation","author":"Yunhao","year":"2023"},{"key":"10.1016\/j.patcog.2026.113515_bib0043","unstructured":"B.N. Bloch, A. Madabhushi, H. Huisman, J. Freymann, J. Kirby, M. Grauer, A. Enquobahrie, C. Jaffe, L. Clarke, K. Farahani, NCI-ISBI 2013 Challenge: automated segmentation of prostate structures, 2015. 10.7937\/K9\/TCIA.2015.ZF0VLOPV."},{"issue":"12","key":"10.1016\/j.patcog.2026.113515_bib0044","doi-asserted-by":"crossref","first-page":"3543","DOI":"10.1109\/TMI.2021.3090082","article-title":"Multi-centre, multi-vendor and multi-disease cardiac segmentation: the M&Ms challenge","volume":"40","author":"Campello","year":"2021","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.113515_bib0045","series-title":"Medical Image Computing and Computer Assisted Intervention","article-title":"Semi-supervised meta-learning with disentanglement for domain-generalised medical image segmentation","author":"Liu","year":"2021"},{"key":"10.1016\/j.patcog.2026.113515_bib0046","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"34","article-title":"Exploring smoothness and class-separation for semi-supervised medical image segmentation","volume":"Vol. 13435","author":"Wu","year":"2022"},{"key":"10.1016\/j.patcog.2026.113515_bib0047","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"98","article-title":"Correlation-aware mutual learning for semi-supervised medical image segmentation","author":"Gao","year":"2023"},{"issue":"10","key":"10.1016\/j.patcog.2026.113515_bib0048","doi-asserted-by":"crossref","first-page":"3909","DOI":"10.1109\/TMI.2025.3532084","article-title":"Stitching, fine-tuning, re-training: a sam-enabled framework for semi-supervised 3D medical image segmentation","volume":"44","author":"Li","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.113515_bib0049","doi-asserted-by":"crossref","unstructured":"Y. Zhang, B. Lv, L. Xue, W. Zhang, Y. Liu, Y. Fu, Y. Cheng, Y. Qi, SemiSAM+: rethinking semi-supervised medical image segmentation in the era of foundation models, arXiv: 2502.20749(2025).","DOI":"10.1016\/j.media.2025.103733"},{"issue":"4","key":"10.1016\/j.patcog.2026.113515_bib0050","doi-asserted-by":"crossref","first-page":"3031","DOI":"10.1109\/TPAMI.2025.3528453","article-title":"UniMatch V2: pushing the limit of semi-supervised semantic segmentation","volume":"47","author":"Yang","year":"2025","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"10.1016\/j.patcog.2026.113515_bib0051","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","article-title":"nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation","volume":"18","author":"Isensee","year":"2021","journal-title":"Nat. Methods"},{"key":"10.1016\/j.patcog.2026.113515_bib0052","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"475","article-title":"Shape-aware meta-learning for generalizing prostate MRI segmentation to unseen domains","author":"Liu","year":"2020"},{"key":"10.1016\/j.patcog.2026.113515_bib0053","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"605","article-title":"Uncertainty-aware self-ensembling model for semi-supervised 3D left atrium segmentation","author":"Yu","year":"2019"},{"key":"10.1016\/j.patcog.2026.113515_bib0054","series-title":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","first-page":"1","article-title":"Semi-supervised domain generalization for medical image analysis","author":"Zhang","year":"2022"},{"key":"10.1016\/j.patcog.2026.113515_bib0055","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.131919","article-title":"MGC-net: semi-supervised domain generalization in medical image segmentation via multi-granularity consistency","volume":"660","author":"Li","year":"2026","journal-title":"Neurocomputing"}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326004814?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326004814?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,4]],"date-time":"2026-04-04T14:08:16Z","timestamp":1775311696000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326004814"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,11]]},"references-count":55,"alternative-id":["S0031320326004814"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113515","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,11]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Boosting cross-domain semi-supervised medical image segmentation with internal and external regularizations","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.113515","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 Ltd.","name":"copyright","label":"Copyright"}],"article-number":"113515"}}