{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T11:18:13Z","timestamp":1783509493722,"version":"3.55.0"},"reference-count":59,"publisher":"Elsevier BV","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"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,12,1]],"date-time":"2026-12-01T00:00:00Z","timestamp":1796083200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","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":[[2026,12]]},"DOI":"10.1016\/j.patcog.2026.114318","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T16:16:26Z","timestamp":1782404186000},"page":"114318","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"PD","title":["MSemi: Adaptive text\u2013image fusion for semi-supervised medical image segmentation"],"prefix":"10.1016","volume":"180","author":[{"given":"Ziyan","family":"Cao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9780-3410","authenticated-orcid":false,"given":"Qing","family":"Cai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ke","family":"Yan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhi","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mei","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiuliang","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.patcog.2026.114318_b1","article-title":"Prompt engineering for healthcare: Methodologies and applications","author":"Wang","year":"2025","journal-title":"Meta-Radiol."},{"key":"10.1016\/j.patcog.2026.114318_b2","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.patcog.2018.05.008","article-title":"An adaptive-scale active contour model for inhomogeneous image segmentation and bias field estimation","volume":"82","author":"Cai","year":"2018","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114318_b3","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2026.113115","article-title":"Adaptive knowledge transferring with switching dual-student framework for semi-supervised medical image segmentation","author":"Nguyen","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114318_b4","article-title":"Enhancing semi-supervised medical image segmentation via semantic transfer","author":"Huang","year":"2026","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114318_b5","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110426","article-title":"Cross co-teaching for semi-supervised medical image segmentation","volume":"152","author":"Zhang","year":"2024","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114318_b6","unstructured":"W. Cai, Y. Huang, Y. Liu, X. Li, Cross-consistency training for semi-supervised medical image segmentation, in: International Conference on Medical Image Computing and Computer-Assisted Intervention, 2021, pp. 202\u2013211."},{"key":"10.1016\/j.patcog.2026.114318_b7","article-title":"Ambiguity-aware pseudo-labeling for semi-supervised medical image segmentation","volume":"85","author":"Lu","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b8","doi-asserted-by":"crossref","unstructured":"Q. Cai, M. Li, D. Ren, J. Lyu, H. Zheng, J. Dong, Y.-H. Yang, Spherical pseudo-cylindrical representation for omnidirectional image super-resolution, in: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 38, 2024, pp. 873\u2013881, 2.","DOI":"10.1609\/aaai.v38i2.27846"},{"key":"10.1016\/j.patcog.2026.114318_b9","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.patcog.2019.04.019","article-title":"Saliency-guided level set model for automatic object segmentation","volume":"93","author":"Cai","year":"2019","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.patcog.2026.114318_b10","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/j.ins.2022.03.035","article-title":"RVLSM: Robust variational level set method for image segmentation with intensity inhomogeneity and high noise","volume":"596","author":"Zhang","year":"2022","journal-title":"Information sciences"},{"key":"10.1016\/j.patcog.2026.114318_b11","article-title":"A survey of deep learning in medical imaging: From pre-trained models to foundation models","volume":"85","author":"Lundervold","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b12","doi-asserted-by":"crossref","unstructured":"Q. Cai, F. Zhang, C. Zhang, Z. Liu, et al., SEMC: Structure-Enhanced Mixture-of-Experts Contrastive Learning for Ultrasound Standard Plane Recognition, in: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 40, 2026, pp. 2543\u20132551, 4.","DOI":"10.1609\/aaai.v40i4.37241"},{"key":"10.1016\/j.patcog.2026.114318_b13","doi-asserted-by":"crossref","first-page":"113456","DOI":"10.1016\/j.patcog.2026.113456","article-title":"Multimodal artificial intelligence for disease diagnosis: advances, applications, and challenges","author":"Cai","year":"2026","journal-title":"Pattern Recognition"},{"key":"10.1016\/j.patcog.2026.114318_b14","doi-asserted-by":"crossref","unstructured":"K. Yan, Q. Cai, F. Zhang, Z. Cao, Z. Liu, SGTC: Semantic-guided triplet co-training for sparsely annotated semi-supervised medical image segmentation, in: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 39, 2025, pp. 9112\u20139120, 9.","DOI":"10.1609\/aaai.v39i9.32986"},{"key":"10.1016\/j.patcog.2026.114318_b15","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.122772","article-title":"DSLSM: Dual-kernel-induced statistic level set model for image segmentation","volume":"242","author":"Zhang","year":"2024","journal-title":"Expert Syst. Appl."},{"key":"10.1016\/j.patcog.2026.114318_b16","article-title":"LearnMat: Semantic-Aware Self-Supervision Fine-Grained Visual Recognition","author":"Li","year":"2026","journal-title":"IEEE Transactions on Image Processing"},{"key":"10.1016\/j.patcog.2026.114318_b17","article-title":"LViT: Language meets vision transformer in medical image segmentation","volume":"85","author":"Li","year":"2023","journal-title":"Med. Image Anal."},{"issue":"1","key":"10.1016\/j.patcog.2026.114318_b18","first-page":"123","article-title":"TextMatch: Text-guided semi-supervised medical image segmentation via textual and visual alignment","volume":"43","author":"Li","year":"2024","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.114318_b19","article-title":"CookGALIP: Recipe controllable generative adversarial CLIPs with sequential ingredient prompts for food image generation","author":"Xu","year":"2024","journal-title":"IEEE Transactions on Multimedia"},{"issue":"3","key":"10.1016\/j.patcog.2026.114318_b20","first-page":"1123","article-title":"Limitations of static text embeddings in medical vision-language models","volume":"28","author":"Zhang","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.patcog.2026.114318_b21","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.2026.114318_b22","article-title":"Dynamic fusion of textual and visual cues for semi-supervised medical image segmentation","volume":"94","author":"Li","year":"2024","journal-title":"Med. Image Anal."},{"issue":"1","key":"10.1016\/j.patcog.2026.114318_b23","first-page":"112","article-title":"Asymmetric vision-language fusion for semi-supervised medical image segmentation","volume":"29","author":"Liu","year":"2025","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.patcog.2026.114318_b24","unstructured":"S. Zhang, Y. Xu, N. Usuyama, PubMedCLIP for semi-supervised medical vision-language tasks, in: Proceedings of the International Conference on Learning Representations, 2024."},{"key":"10.1016\/j.patcog.2026.114318_b25","article-title":"MedKLIP: Enhancing medical image segmentation with knowledge-aware language-image pretraining","volume":"96","author":"Zhou","year":"2025","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b26","doi-asserted-by":"crossref","unstructured":"C. Zheng, C. Tian, J. Wen, D. Zhang, Q. Zhu, HeLo: Heterogeneous multi-modal fusion with label correlation for emotion distribution learning, in: Proceedings of the 33rd ACM International Conference on Multimedia, 2025, pp. 5519\u20135527.","DOI":"10.1145\/3746027.3754852"},{"key":"10.1016\/j.patcog.2026.114318_b27","doi-asserted-by":"crossref","DOI":"10.1109\/TMI.2026.3654000","article-title":"Adjacent-aware modality recovery based on incomplete multi-modal brain disease diagnosis","author":"Cui","year":"2026","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.114318_b28","article-title":"Multi-modal brain network fusion for intelligent diagnostic devices","author":"Li","year":"2025","journal-title":"IEEE Trans. Consum. Electron."},{"key":"10.1016\/j.patcog.2026.114318_b29","series-title":"Proceedings of the International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"692","article-title":"Vclipseg: Voxel-wise CLIP-enhanced model for semi-supervised medical image segmentation","author":"Li","year":"2024"},{"issue":"1","key":"10.1016\/j.patcog.2026.114318_b30","first-page":"312","article-title":"On the asymmetry of vision-language fusion in medical image segmentation","volume":"28","author":"Liu","year":"2024","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"10.1016\/j.patcog.2026.114318_b31","article-title":"GraphMSR: A graph foundation model-based approach for MRI image super-resolution with multimodal semantic integration","author":"Qin","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114318_b32","doi-asserted-by":"crossref","first-page":"48","DOI":"10.1109\/RBME.2020.2992838","article-title":"Wearable sensing and telehealth technology with potential applications in the coronavirus pandemic","volume":"14","author":"Ding","year":"2020","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"10.1016\/j.patcog.2026.114318_b33","article-title":"MMIFprompt: Efficient modality-aware prompting for multimodal medical image fusion","author":"Wei","year":"2025","journal-title":"Pattern Recognit."},{"key":"10.1016\/j.patcog.2026.114318_b34","series-title":"MedSAM: Segment anything in medical images","author":"Ma","year":"2024"},{"key":"10.1016\/j.patcog.2026.114318_b35","series-title":"Un-sam: Universal prompt-free segmentation for generalized nuclei images","author":"Chen","year":"2024"},{"key":"10.1016\/j.patcog.2026.114318_b36","unstructured":"E.J. Hu, Y. Shen, P. Wallis, Z. Allen-Zhu, Y. Li, S. Wang, L. Wang, W. Chen, LoRA: Low-rank adaptation of large language models, in: International Conference on Learning Representations, 2022."},{"issue":"4","key":"10.1016\/j.patcog.2026.114318_b37","first-page":"1456","article-title":"SAM-CT: Segment anything model for computed tomography","volume":"52","author":"Wang","year":"2025","journal-title":"Med. Phys."},{"issue":"9","key":"10.1016\/j.patcog.2026.114318_b38","doi-asserted-by":"crossref","first-page":"2337","DOI":"10.1007\/s11263-022-01653-1","article-title":"Learning to prompt for vision-language models","volume":"130","author":"Zhou","year":"2022","journal-title":"Int. J. Comput. Vis."},{"issue":"10","key":"10.1016\/j.patcog.2026.114318_b39","first-page":"2485","article-title":"Mutual consistency regularization for semi-supervised multi-modal medical image segmentation","volume":"42","author":"Wu","year":"2023","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.114318_b40","article-title":"Bilateral consistency learning for semi-supervised medical image segmentation","volume":"89","author":"Bai","year":"2023","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b41","article-title":"Causal semi-supervised learning with domain adaptation for medical image segmentation","volume":"92","author":"Miao","year":"2024","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b42","unstructured":"Y. Zhang, W. Cai, X. Li, Adaptive pseudo-labeling for semi-supervised 3D medical image segmentation, in: International Conference on Medical Image Computing and Computer-Assisted Intervention, 2022, pp. 512\u2013521."},{"key":"10.1016\/j.patcog.2026.114318_b43","series-title":"Advances in Neural Information Processing Systems","first-page":"596","article-title":"Fixmatch: Simplifying semi-supervised learning with consistency and confidence","volume":"vol. 33","author":"Sohn","year":"2020"},{"key":"10.1016\/j.patcog.2026.114318_b44","doi-asserted-by":"crossref","unstructured":"L. Yu, W. Wang, S. Wang, J. Qin, Uncertainty-aware self-ensembling model for semi-supervised 3D left atrium segmentation, in: International Conference on Medical Image Computing and Computer-Assisted Intervention, 2019, pp. 605\u2013613.","DOI":"10.1007\/978-3-030-32245-8_67"},{"key":"10.1016\/j.patcog.2026.114318_b45","article-title":"Mutual consistency learning for semi-supervised medical image segmentation","volume":"81","author":"Wu","year":"2022","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b46","series-title":"Medical Image Computing and Computer Assisted Intervention","first-page":"297","article-title":"Semi-supervised left atrium segmentation with mutual consistency training","author":"Wu","year":"2022"},{"issue":"12","key":"10.1016\/j.patcog.2026.114318_b47","first-page":"3653","article-title":"MC-Net+: Multi-modal multi-level network for multi-class segmentation of brain tissues","volume":"41","author":"Wu","year":"2022","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.114318_b48","unstructured":"L. Chi, Z. Jiang, Y. Li, H. Wang, Z. Ge, Y. Zheng, Ambiguity-aware bilateral domain adaptation for semi-supervised medical image segmentation, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2023, pp. 12345\u201312354."},{"key":"10.1016\/j.patcog.2026.114318_b49","series-title":"International Conference on Medical Image Computing and Computer-Assisted Intervention","first-page":"56","article-title":"Diffrect: Latent diffusion label rectification for semi-supervised medical image segmentation","author":"Liu","year":"2024"},{"key":"10.1016\/j.patcog.2026.114318_b50","series-title":"2024 IEEE International Conference on Bioinformatics and Biomedicine","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.2026.114318_b51","doi-asserted-by":"crossref","DOI":"10.1016\/j.bspc.2023.105694","article-title":"Contour-aware consistency for semi-supervised medical image segmentation","volume":"89","author":"Li","year":"2024","journal-title":"Biomed. Signal Process. Control."},{"key":"10.1016\/j.patcog.2026.114318_b52","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2024.103450","article-title":"Semi-supervised medical image segmentation via weak-to-strong perturbation consistency and edge-aware contrastive representation","volume":"101","author":"Yang","year":"2025","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b53","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2022.102517","article-title":"Semi-supervised medical image segmentation via uncertainty rectified pyramid consistency","volume":"80","author":"Luo","year":"2022","journal-title":"Med. Image Anal."},{"key":"10.1016\/j.patcog.2026.114318_b54","article-title":"Semi-supervised medical image segmentation using cross-level consistency and pseudo-labeling","volume":"83","author":"Liu","year":"2023","journal-title":"Med. Image Anal."},{"issue":"2","key":"10.1016\/j.patcog.2026.114318_b55","first-page":"567","article-title":"Text-guided semi-supervised segmentation with multi-level alignment","volume":"44","author":"Li","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.114318_b56","doi-asserted-by":"crossref","unstructured":"Y. Ouali, C. Hudelot, M. Tami, Semi-supervised semantic segmentation with cross-consistency training, in: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, 2020, pp. 12674\u201312684.","DOI":"10.1109\/CVPR42600.2020.01269"},{"key":"10.1016\/j.patcog.2026.114318_b57","series-title":"Medical Image Computing and Computer Assisted Intervention","first-page":"635","article-title":"Adaptive cross-modal attention for semi-supervised medical image segmentation","author":"Zhang","year":"2024"},{"issue":"5","key":"10.1016\/j.patcog.2026.114318_b58","doi-asserted-by":"crossref","first-page":"2295","DOI":"10.1109\/TMI.2025.3530097","article-title":"Learnable prompting sam-induced knowledge distillation for semi-supervised medical image segmentation","volume":"44","author":"Huang","year":"2025","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.patcog.2026.114318_b59","article-title":"CauSSL: Causality-inspired semi-supervised learning for medical image segmentation","volume":"90","author":"Miao","year":"2023","journal-title":"Med. Image Anal."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326012835?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320326012835?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T10:48:29Z","timestamp":1783507709000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320326012835"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,12]]},"references-count":59,"alternative-id":["S0031320326012835"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114318","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2026,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"MSemi: Adaptive text\u2013image fusion for semi-supervised medical image segmentation","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2026.114318","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"114318"}}