{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T13:03:54Z","timestamp":1789650234286,"version":"4.0.0"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T00:00:00Z","timestamp":1762387200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100017607","name":"Shenzhen Fundamental Research Program","doi-asserted-by":"publisher","award":["JCYJ20220530153408019"],"award-info":[{"award-number":["JCYJ20220530153408019"]}],"id":[{"id":"10.13039\/501100017607","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100017622","name":"Shenzhen Research and Development Program","doi-asserted-by":"publisher","award":["JCYJ20200109114812361"],"award-info":[{"award-number":["JCYJ20200109114812361"]}],"id":[{"id":"10.13039\/501100017622","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61401451"],"award-info":[{"award-number":["61401451"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J CARS"],"DOI":"10.1007\/s11548-025-03538-3","type":"journal-article","created":{"date-parts":[[2025,11,6]],"date-time":"2025-11-06T12:16:07Z","timestamp":1762431367000},"page":"1867-1877","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A label-aware diffusion model for weakly supervised deformable registration of multimodal MRI\u2013TRUS in prostate cancer"],"prefix":"10.1007","volume":"21","author":[{"given":"Zhirong","family":"Yao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiajun","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1880-4202","authenticated-orcid":false,"given":"Tiexiang","family":"Wen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,6]]},"reference":[{"key":"3538_CR1","doi-asserted-by":"publisher","first-page":"7","DOI":"10.3322\/caac.21708","volume":"72","author":"RL Siegel","year":"2022","unstructured":"Siegel RL, Miller KD, Fuchs HE, Jemal A (2022) Cancer statistics, 2022. CA Cancer J Clin 72:7\u201333. https:\/\/doi.org\/10.3322\/caac.21708","journal-title":"CA Cancer J Clin"},{"key":"3538_CR2","doi-asserted-by":"publisher","first-page":"229","DOI":"10.3322\/caac.21834","volume":"74","author":"F Bray","year":"2024","unstructured":"Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, Jemal A (2024) Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 74:229\u2013263. https:\/\/doi.org\/10.3322\/caac.21834","journal-title":"CA Cancer J Clin"},{"key":"3538_CR3","doi-asserted-by":"publisher","first-page":"2176","DOI":"10.1007\/s00261-019-02391-8","volume":"45","author":"CJ Das","year":"2020","unstructured":"Das CJ, Razik A, Netaji A, Verma S (2020) Prostate MRI\u2013TRUS fusion biopsy: a review of the state of the art procedure. Abdom Radiol 45:2176\u20132183. https:\/\/doi.org\/10.1007\/s00261-019-02391-8","journal-title":"Abdom Radiol"},{"key":"3538_CR4","doi-asserted-by":"publisher","first-page":"106767","DOI":"10.1016\/j.compeleceng.2020.106767","volume":"87","author":"HR Boveiri","year":"2020","unstructured":"Boveiri HR, Khayami R, Javidan R, Mehdizadeh A (2020) Medical image registration using deep neural networks: a comprehensive review. Comput Electr Eng 87:106767. https:\/\/doi.org\/10.1016\/j.compeleceng.2020.106767","journal-title":"Comput Electr Eng"},{"key":"3538_CR5","doi-asserted-by":"publisher","first-page":"2269","DOI":"10.1007\/s11548-024-03258-0","volume":"19","author":"S Liu","year":"2024","unstructured":"Liu S, Wei G, Fan Y, Chen L, Zhang Z (2024) Multimodal registration network with multi-scale feature-crossing. Int J Comput Assist Radiol Surg 19:2269\u20132278. https:\/\/doi.org\/10.1007\/s11548-024-03258-0","journal-title":"Int J Comput Assist Radiol Surg"},{"key":"3538_CR6","doi-asserted-by":"publisher","unstructured":"Chen Z, Wei J, Li R (2022) Unsupervised multi-modal medical image registration via discriminator-free image-to-image translation. In: Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 834\u2013840. https:\/\/doi.org\/10.24963\/ijcai.2022\/117.","DOI":"10.24963\/ijcai.2022\/117"},{"key":"3538_CR7","doi-asserted-by":"publisher","first-page":"2229","DOI":"10.1109\/TMI.2024.3362968","volume":"43","author":"H Wang","year":"2024","unstructured":"Wang H, Ni D, Wang Y (2024) Recursive deformable pyramid network for unsupervised medical image registration. IEEE Trans Med Imaging 43:2229\u20132240. https:\/\/doi.org\/10.1109\/TMI.2024.3362968","journal-title":"IEEE Trans Med Imaging"},{"key":"3538_CR8","doi-asserted-by":"publisher","first-page":"1788","DOI":"10.1109\/TMI.2019.2897538","volume":"38","author":"G Balakrishnan","year":"2019","unstructured":"Balakrishnan G, Zhao A, Sabuncu MR, Guttag J, Dalca AV (2019) Voxelmorph: a learning framework for deformable medical image registration. IEEE Trans Med Imaging 38:1788\u20131800. https:\/\/doi.org\/10.1109\/TMI.2019.2897538","journal-title":"IEEE Trans Med Imaging"},{"key":"3538_CR9","doi-asserted-by":"publisher","first-page":"107598","DOI":"10.1016\/j.compbiomed.2023.107598","volume":"167","author":"X Ma","year":"2023","unstructured":"Ma X, He J, Liu X, Liu Q, Chen G, Yuan B, Li C, Xia Y (2023) Hierarchical cumulative network for unsupervised medical image registration. Comput Biol Med 167:107598. https:\/\/doi.org\/10.1016\/j.compbiomed.2023.107598","journal-title":"Comput Biol Med"},{"key":"3538_CR10","doi-asserted-by":"publisher","first-page":"102263","DOI":"10.1016\/j.compmedimag.2023.102263","volume":"108","author":"X Ma","year":"2023","unstructured":"Ma X, Cui H, Li S, Yang Y, Xia Y (2023) Deformable medical image registration with global\u2013local transformation network and region similarity constraint. Comput Med Imaging Graph 108:102263. https:\/\/doi.org\/10.1016\/j.compmedimag.2023.102263","journal-title":"Comput Med Imaging Graph"},{"key":"3538_CR11","doi-asserted-by":"publisher","unstructured":"Qin Y, Li X (2023) FSDiffReg: Feature-wise and score-wise diffusion-guided unsupervised deformable image registration for cardiac images. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, p 655\u2013665. https:\/\/doi.org\/10.1007\/978-3-031-43999-5_62","DOI":"10.1007\/978-3-031-43999-5_62"},{"issue":"12","key":"3538_CR12","doi-asserted-by":"publisher","first-page":"4895","DOI":"10.21037\/qims-21-175","volume":"11","author":"H Xiao","year":"2021","unstructured":"Xiao H, Teng X, Liu C, Li T, Ren G, Yang R, Shen D, Cai J (2021) A review of deep learning-based three-dimensional medical image registration methods. Quant Imaging Med Surg 11(12):4895\u20134916. https:\/\/doi.org\/10.21037\/qims-21-175","journal-title":"Quant Imaging Med Surg"},{"key":"3538_CR13","doi-asserted-by":"publisher","first-page":"102811","DOI":"10.1016\/j.media.2023.102811","volume":"88","author":"HG Khor","year":"2023","unstructured":"Khor HG, Ning G, Sun Y, Lu X, Zhang X, Liao H (2023) Anatomically constrained and attention-guided deep feature fusion for joint segmentation and deformable medical image registration. Med Image Anal 88:102811. https:\/\/doi.org\/10.1016\/j.media.2023.102811","journal-title":"Med Image Anal"},{"key":"3538_CR14","doi-asserted-by":"publisher","first-page":"1177","DOI":"10.1109\/JBHI.2021.3095409","volume":"26","author":"Y He","year":"2021","unstructured":"He Y, Li T, Ge R, Yang J, Kong Y, Zhu J, Shu H, Yang G, Li S (2021) Few-shot learning for deformable medical image registration with perception-correspondence decoupling and reverse teaching. IEEE J Biomed Health Inform 26:1177\u20131187. https:\/\/doi.org\/10.1109\/JBHI.2021.3095409","journal-title":"IEEE J Biomed Health Inform"},{"key":"3538_CR15","doi-asserted-by":"publisher","first-page":"111338","DOI":"10.1016\/j.patcog.2024.111338","volume":"161","author":"M Meng","year":"2025","unstructured":"Meng M, Fulham M, Feng D, Bi L, Kim J (2025) Autofuse: automatic fusion networks for deformable medical image registration. Pattern Recogn 161:111338. https:\/\/doi.org\/10.1016\/j.patcog.2024.111338","journal-title":"Pattern Recogn"},{"key":"3538_CR16","doi-asserted-by":"publisher","first-page":"95551","DOI":"10.1109\/ACCESS.2021.3091011","volume":"9","author":"MS Elmahdy","year":"2021","unstructured":"Elmahdy MS, Beljaards L, Yousefi S, Sokooti H, Verbeek F, Van Der Heide UA, Staring M (2021) Joint registration and segmentation via multi-task learning for adaptive radiotherapy of prostate cancer. IEEE Access 9:95551\u201395568. https:\/\/doi.org\/10.1109\/ACCESS.2021.3091011","journal-title":"IEEE Access"},{"key":"3538_CR17","doi-asserted-by":"publisher","unstructured":"Hering A, Kuckertz S, Heldmann S, Heinrich MP (2019) Enhancing label-driven deep deformable image registration with local distance metrics for state-of-the-art cardiac motion tracking. In: Bildverarbeitung f\u00fcr die Medizin 2019: Algorithmen\u2013Systeme\u2013Anwendungen. Proceedings des Workshops vom 17. bis 19. M\u00e4rz 2019 in L\u00fcbeck. Springer, p 309\u2013314. https:\/\/doi.org\/10.1007\/978-3-658-25326-4_69","DOI":"10.1007\/978-3-658-25326-4_69"},{"issue":"13","key":"3538_CR18","doi-asserted-by":"publisher","first-page":"135002","DOI":"10.1088\/1361-6560\/ab8cd6","volume":"65","author":"Q Zeng","year":"2020","unstructured":"Zeng Q, Fu Y, Tian Z, Lei Y, Zhang Y, Wang T, Mao H, Liu T, Curran WJ, Jani AB, Patel P, Yang X (2020) Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy. Phys Med Biol 65(13):135002. https:\/\/doi.org\/10.1088\/1361-6560\/ab8cd6","journal-title":"Phys Med Biol"},{"key":"3538_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.media.2018.07.002","volume":"49","author":"Y Hu","year":"2018","unstructured":"Hu Y, Modat M, Gibson E, Li W, Ghavami N, Bonmati E, Wang G, Bandula S, Moore CM, Emberton M, Ourselin S, Noble JA, Barratt DC, Vercauteren T (2018) Weakly-supervised convolutional neural networks for multimodal image registration. Med Image Anal 49:1\u201313. https:\/\/doi.org\/10.1016\/j.media.2018.07.002","journal-title":"Med Image Anal"},{"issue":"8","key":"3538_CR20","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1002\/acm2.13292","volume":"22","author":"P McGeachy","year":"2021","unstructured":"McGeachy P, Watt E, Husain S, Martell K, Martinez P, Sawhney S, Thind K (2021) MRI-TRUS registration methodology for TRUS-guided HDR prostate brachytherapy. J Appl Clin Med Phys 22(8):284\u2013294. https:\/\/doi.org\/10.1002\/acm2.13292","journal-title":"J Appl Clin Med Phys"},{"key":"3538_CR21","doi-asserted-by":"publisher","unstructured":"Baum Z, Saeed S, Min Z, Hu Y, Barratt DC (2023) MR to ultrasound registration for prostate challenge-dataset. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2023. Zenodo, Zenodo. https:\/\/doi.org\/10.5281\/zenodo.7844907","DOI":"10.5281\/zenodo.7844907"}],"container-title":["International Journal of Computer Assisted Radiology and Surgery"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-025-03538-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11548-025-03538-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11548-025-03538-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T12:18:16Z","timestamp":1789647496000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11548-025-03538-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,6]]},"references-count":21,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["3538"],"URL":"https:\/\/doi.org\/10.1007\/s11548-025-03538-3","relation":{},"ISSN":["1861-6429"],"issn-type":[{"value":"1861-6429","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,6]]},"assertion":[{"value":"27 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare that they have no conflict of interest.","order":1,"name":"Ethics","label":"Conflict of interest:","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study used only publicly available and anonymized datasets and therefore did not require additional ethical approval.","order":2,"name":"Ethics","label":"Ethical approval:","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No informed consent was required for this study.","order":3,"name":"Ethics","label":"Informed consent","group":{"name":"EthicsHeading","label":"Declarations"}}]}}