{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T15:01:22Z","timestamp":1777042882786,"version":"3.51.4"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T00:00:00Z","timestamp":1736553600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T00:00:00Z","timestamp":1736553600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972227"],"award-info":[{"award-number":["61972227"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Talent Introduction and Cultivation Plan in Colleges and Universities of Shandong Province"},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2022MF245"],"award-info":[{"award-number":["ZR2022MF245"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Youth Innovation Team in Colleges and universities of Shandong Province","award":["2022KJ185"],"award-info":[{"award-number":["2022KJ185"]}]},{"name":"Shandong Province Natural Science Fundation Youth Branch","award":["ZR2023QF161"],"award-info":[{"award-number":["ZR2023QF161"]}]},{"name":"Jinan Scientific Research Leader Studio","award":["202228105"],"award-info":[{"award-number":["202228105"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s10489-025-06232-8","type":"journal-article","created":{"date-parts":[[2025,1,11]],"date-time":"2025-01-11T08:01:52Z","timestamp":1736582512000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Cyclic deformable medical image registration with prompt: deep fusion of diffeomorphic and transformer methods"],"prefix":"10.1007","volume":"55","author":[{"given":"Longhao","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1237-6035","authenticated-orcid":false,"given":"Yunfeng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fangxun","family":"Bao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xunxiang","family":"Yao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Caiming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,11]]},"reference":[{"key":"6232_CR1","doi-asserted-by":"crossref","unstructured":"Zhang Y, Pei Y, Zha H (2021) Learning dual transformer network for diffeomorphic registration[C], Medical Image Computing and Computer Assisted Intervention?MICCAI: 24th International Conference, Strasbourg, France, September 27?October 1, 2021, Proceedings, Part IV 24. Springer International Publishing 2021:129\u2013138","DOI":"10.1007\/978-3-030-87202-1_13"},{"key":"6232_CR2","doi-asserted-by":"publisher","first-page":"107171","DOI":"10.1016\/j.patcog.2019.107171","volume":"100","author":"D Wei","year":"2020","unstructured":"Wei D, Zhang L, Wu Z et al (2020) Deep morphological simplification network (MS-Net) for guided registration of brain magnetic resonance images[J]. Pattern Recogn 100:107171","journal-title":"Pattern Recogn"},{"issue":"1","key":"6232_CR3","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","volume":"12","author":"BB Avants","year":"2008","unstructured":"Avants BB, Epstein CL, Grossman M et al (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain[J]. Med Image Anal 12(1):26\u201341","journal-title":"Med Image Anal"},{"issue":"7","key":"6232_CR4","doi-asserted-by":"publisher","first-page":"1239","DOI":"10.1109\/TMI.2013.2246577","volume":"32","author":"MP Heinrich","year":"2013","unstructured":"Heinrich MP, Jenkinson M, Brady M et al (2013) MRF-based deformable registration and ventilation estimation of lung CT[J]. IEEE Trans Med Imaging 32(7):1239\u20131248","journal-title":"IEEE Trans Med Imaging"},{"issue":"1","key":"6232_CR5","first-page":"012003","volume":"3","author":"X Chen","year":"2021","unstructured":"Chen X, Diaz-Pinto A, Ravikumar N et al (2021) Deep learning in medical image registration[J]. Progress in Biomedical Engineering 3(1):012003","journal-title":"Progress in Biomedical Engineering"},{"key":"6232_CR6","doi-asserted-by":"crossref","unstructured":"Yin C, Zhang Q, Ren W (2022) A new semantic edge aware network for object affordance detection[J]. J Intell Robotic Syst 104(1):2","DOI":"10.1007\/s10846-021-01525-9"},{"key":"6232_CR7","doi-asserted-by":"crossref","unstructured":"Huang G, Liu Z, Van Der Maaten L, et al (2017) Densely connected convolutional networks[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition: 4700-4708","DOI":"10.1109\/CVPR.2017.243"},{"key":"6232_CR8","doi-asserted-by":"crossref","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation[C]\/\/Medical Image Computing and Computer-Assisted Intervention, MICCAI: 18th International Conference, Munich, Germany, October 5\u20139, 2015, Proceedings, Part III 18. Springer International Publishing 2015:234\u2013241","DOI":"10.1007\/978-3-319-24574-4_28"},{"issue":"2","key":"6232_CR9","doi-asserted-by":"publisher","first-page":"103223","DOI":"10.1016\/j.ipm.2022.103223","volume":"60","author":"Z Zhu","year":"2023","unstructured":"Zhu Z, Zhang D, Li L et al (2023) Knowledge-guided multi-granularity GCN for ABSA[J]. Information Processing & Management 60(2):103223","journal-title":"Information Processing & Management"},{"key":"6232_CR10","doi-asserted-by":"crossref","unstructured":"Mok T C W, Chung A (2022) Affine medical image registration with coarse-to-fine vision transformer[C]\/\/Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition: 20835-20844","DOI":"10.1109\/CVPR52688.2022.02017"},{"key":"6232_CR11","doi-asserted-by":"crossref","unstructured":"Han K, Sun S, Yan X, et al (2023) Diffeomorphic image registration with neural velocity field[C]\/\/Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision: 1869-1879","DOI":"10.1109\/WACV56688.2023.00191"},{"key":"6232_CR12","doi-asserted-by":"crossref","unstructured":"Mok T C W, Chung A (2020) Fast symmetric diffeomorphic image registration with convolutional neural networks[C]\/\/Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition: 4644-4653","DOI":"10.1109\/CVPR42600.2020.00470"},{"issue":"8","key":"6232_CR13","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 et al (2019) VoxelMorph: a learning framework for deformable medical image registration[J]. IEEE Trans Med Imaging 38(8):1788\u20131800","journal-title":"IEEE Trans Med Imaging"},{"issue":"6","key":"6232_CR14","doi-asserted-by":"publisher","first-page":"2828","DOI":"10.3390\/app12062828","volume":"12","author":"S Liu","year":"2022","unstructured":"Liu S, Yang B, Wang Y et al (2022) 2D\/3D multimode medical image registration based on normalized cross-correlation[J]. Appl Sci 12(6):2828","journal-title":"Appl Sci"},{"key":"6232_CR15","doi-asserted-by":"publisher","first-page":"24528","DOI":"10.1109\/ACCESS.2022.3154771","volume":"10","author":"S Mohanty","year":"2022","unstructured":"Mohanty S, Dakua SP (2022) Toward computing cross-modality symmetric non-rigid medical image registration[J]. IEEE Access 10:24528\u201324539","journal-title":"IEEE Access"},{"key":"6232_CR16","doi-asserted-by":"publisher","first-page":"106335","DOI":"10.1016\/j.asoc.2020.106335","volume":"93","author":"Y Chen","year":"2020","unstructured":"Chen Y, He F, Li H et al (2020) A full migration BBO algorithm with enhanced population quality bounds for multimodal biomedical image registration[J]. Appl Soft Comput 93:106335","journal-title":"Appl Soft Comput"},{"issue":"2","key":"6232_CR17","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1109\/TMI.2016.2610583","volume":"36","author":"V Vishnevskiy","year":"2016","unstructured":"Vishnevskiy V, Gass T, Szekely G et al (2016) Isotropic total variation regularization of displacements in parametric image registration[J]. IEEE Trans Med Imaging 36(2):385\u2013395","journal-title":"IEEE Trans Med Imaging"},{"key":"6232_CR18","first-page":"137","volume-title":"Implicitly Solved Regularization for Learning-Based Image Registration[C]\/\/International Workshop on Machine Learning in Medical Imaging","author":"J Ehrhardt","year":"2023","unstructured":"Ehrhardt J, Handels H (2023) Implicitly Solved Regularization for Learning-Based Image Registration[C]\/\/International Workshop on Machine Learning in Medical Imaging. Springer Nature Switzerland, Cham, pp 137\u2013146"},{"key":"6232_CR19","doi-asserted-by":"crossref","unstructured":"Xu Z, Niethammer M (2019) DeepAtlas: Joint semi-supervised learning of image registration and segmentation[C]\/\/Medical Image Computing and Computer Assisted Intervention MICCAI: 22nd International Conference, Shenzhen, China, October 2019, Proceedings, Part II 22. Springer International Publishing 2019:420\u2013429","DOI":"10.1007\/978-3-030-32245-8_47"},{"key":"6232_CR20","doi-asserted-by":"publisher","first-page":"101822","DOI":"10.1016\/j.media.2020.101822","volume":"67","author":"M Blendowski","year":"2021","unstructured":"Blendowski M, Hansen L, Heinrich MP (2021) Weakly-supervised learning of multi-modal features for regularised iterative descent in 3D image registration[J]. Med Image Anal 67:101822","journal-title":"Med Image Anal"},{"key":"6232_CR21","doi-asserted-by":"crossref","unstructured":"Cao X, Yang J, Wang L, et al (2018) Deep learning based inter-modality image registration supervised by intra-modality similarity[C]\/\/Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings 9. Springer International Publishing: 55-63","DOI":"10.1007\/978-3-030-00919-9_7"},{"key":"6232_CR22","doi-asserted-by":"crossref","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation[C]\/\/Medical Image Computing and Computer-Assisted Intervention, MICCAI: 18th International Conference, Munich, Germany, October 5\u20139, 2015, Proceedings, Part III 18. Springer International Publishing 2015:234\u2013241","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"6232_CR23","doi-asserted-by":"crossref","unstructured":"Dey N, Ren M, Dalca A V, et al (2021) Generative adversarial registration for improved conditional deformable templates[C]\/\/Proceedings of the IEEE\/CVF international conference on computer vision: 3929-3941","DOI":"10.1109\/ICCV48922.2021.00390"},{"key":"6232_CR24","doi-asserted-by":"crossref","unstructured":"Chen J, Xie Y, Wang K (2018) Generative invertible networks (GIN): Pathophysiology-interpretable feature mapping and virtual patient generation[C]\/\/Medical Image Computing and Computer Assisted Intervention, MICCAI: 21st International Conference, Granada, Spain, September 16\u201320, 2018, Proceedings, Part I. Springer International Publishing 2018:537\u2013545","DOI":"10.1007\/978-3-030-00928-1_61"},{"key":"6232_CR25","doi-asserted-by":"publisher","first-page":"102036","DOI":"10.1016\/j.media.2021.102036","volume":"71","author":"B Kim","year":"2021","unstructured":"Kim B, Kim DH, Park SH et al (2021) CycleMorph: cycle consistent unsupervised deformable image registration[J]. Med Image Anal 71:102036","journal-title":"Med Image Anal"},{"key":"6232_CR26","doi-asserted-by":"crossref","unstructured":"Azad R, Kazerouni A, Heidari M, et al (2023) Advances in medical image analysis with vision transformers: a comprehensive review[J]. Medical Image Analysis:103000","DOI":"10.1016\/j.media.2023.103000"},{"key":"6232_CR27","doi-asserted-by":"publisher","first-page":"102615","DOI":"10.1016\/j.media.2022.102615","volume":"82","author":"J Chen","year":"2022","unstructured":"Chen J, Frey EC, He Y et al (2022) Transmorph: Transformer for unsupervised medical image registration[J]. Med Image Anal 82:102615","journal-title":"Med Image Anal"},{"key":"6232_CR28","doi-asserted-by":"crossref","unstructured":"Mok TCW, Chung ACS (2020) Large deformation diffeomorphic image registration with laplacian pyramid networks[C], , Medical Image Computing and Computer Assisted Intervention?MICCAI: 23rd International Conference, Lima, Peru, October 2020, Proceedings, Part III 23. Springer International Publishing 2020:211\u2013221","DOI":"10.1007\/978-3-030-59716-0_21"},{"key":"6232_CR29","doi-asserted-by":"crossref","unstructured":"Han K, Sun S, Yan X, et al (2023) Diffeomorphic image registration with neural velocity field[C]\/\/Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision: 1869-1879","DOI":"10.1109\/WACV56688.2023.00191"},{"key":"6232_CR30","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.media.2019.07.006","volume":"57","author":"AV Dalca","year":"2019","unstructured":"Dalca AV, Balakrishnan G, Guttag J et al (2019) Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces[J]. Med Image Anal 57:226\u2013236","journal-title":"Med Image Anal"},{"key":"6232_CR31","unstructured":"Vaswani A, Shazeer N, Parmar N, et al (2017) Attention is all you need[J]. Advances in neural information processing systems, 30"},{"key":"6232_CR32","unstructured":"Dosovitskiy A, Beyer L, Kolesnikov A, et al (2020) An image is worth 16x16 words: Transformers for image recognition at scale[J]. arXiv:2010.11929"},{"key":"6232_CR33","doi-asserted-by":"crossref","unstructured":"Kirillov A, Mintun E, Ravi N, et al (2023) Segment anything[C]\/\/Proceedings of the IEEE\/CVF International Conference on Computer Vision: 4015-4026","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"6232_CR34","unstructured":"Radford A, Kim J W, Hallacy C, et al (2021) Learning transferable visual models from natural language supervision[C]\/\/International conference on machine learning. PMLR: 8748-8763"},{"key":"6232_CR35","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y, et al (2021) Swin transformer: Hierarchical vision transformer using shifted windows[C]\/\/Proceedings of the IEEE\/CVF international conference on computer vision: 10012-10022","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"6232_CR36","first-page":"12116","volume":"34","author":"M Raghu","year":"2021","unstructured":"Raghu M, Unterthiner T, Kornblith S et al (2021) Do vision transformers see like convolutional neural networks?[J]. Adv Neural Inf Process Syst 34:12116\u201312128","journal-title":"Adv Neural Inf Process Syst"},{"key":"6232_CR37","doi-asserted-by":"crossref","unstructured":"Isola P, Zhu J Y, Zhou T, et al (2017) Image-to-image translation with conditional adversarial networks[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition: 1125-1134","DOI":"10.1109\/CVPR.2017.632"},{"key":"6232_CR38","unstructured":"Jaderberg M, Simonyan K, Zisserman A (2015) Spatial transformer networks[J]. Advances in neural information processing systems, 28"},{"issue":"1","key":"6232_CR39","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","volume":"12","author":"BB Avants","year":"2008","unstructured":"Avants BB, Epstein CL, Grossman M et al (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain[J]. Med Image Anal 12(1):26\u201341","journal-title":"Med Image Anal"},{"key":"6232_CR40","unstructured":"Heinrich M P, Maier O, Handels H (2015) Multi-modal Multi-Atlas Segmentation using Discrete Optimisation and Self-Similarities[J]. VISCERAL Challenge@ ISBI, 1390: 27"},{"key":"6232_CR41","doi-asserted-by":"crossref","unstructured":"Ronchetti M, Wein W, Navab N, et al (2023) Disa: Differentiable similarity approximation for universal multimodal registration[C]\/\/International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer Nature Switzerland: 761-770","DOI":"10.1007\/978-3-031-43999-5_72"},{"key":"6232_CR42","unstructured":"Paszke A, Gross S, Massa F, et al (2019) Pytorch: an imperative style, high-performance deep learning library[J]. Advances in neural information processing systems, 32"},{"issue":"3","key":"6232_CR43","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1109\/TMI.2021.3116879","volume":"41","author":"M Hoffmann","year":"2021","unstructured":"Hoffmann M, Billot B, Greve DN et al (2021) SynthMorph: learning contrast-invariant registration without acquired images[J]. IEEE Trans Med Imaging 41(3):543\u2013558","journal-title":"IEEE Trans Med Imaging"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06232-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-025-06232-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-025-06232-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T14:54:57Z","timestamp":1738335297000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-025-06232-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,11]]},"references-count":43,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["6232"],"URL":"https:\/\/doi.org\/10.1007\/s10489-025-06232-8","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,11]]},"assertion":[{"value":"28 December 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 January 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The research does not involve any human participants or animals, and the authors don\u2019t use any data that require informed consent.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"296"}}