{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:07:06Z","timestamp":1778256426329,"version":"3.51.4"},"publisher-location":"Cham","reference-count":27,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031720680","type":"print"},{"value":"9783031720697","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-3-031-72069-7_71","type":"book-chapter","created":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T19:02:59Z","timestamp":1727982179000},"page":"761-771","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["WiNet: Wavelet-Based Incremental Learning for\u00a0Efficient Medical Image Registration"],"prefix":"10.1007","author":[{"given":"Xinxing","family":"Cheng","sequence":"first","affiliation":[]},{"given":"Xi","family":"Jia","sequence":"additional","affiliation":[]},{"given":"Wenqi","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Qiufu","family":"Li","sequence":"additional","affiliation":[]},{"given":"Linlin","family":"Shen","sequence":"additional","affiliation":[]},{"given":"Alexander","family":"Krull","sequence":"additional","affiliation":[]},{"given":"Jinming","family":"Duan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,10,4]]},"reference":[{"issue":"1","key":"71_CR1","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1016\/j.neuroimage.2007.07.007","volume":"38","author":"J Ashburner","year":"2007","unstructured":"Ashburner, J.: A fast diffeomorphic image registration algorithm. Neuroimage 38(1), 95\u2013113 (2007)","journal-title":"Neuroimage"},{"issue":"1","key":"71_CR2","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.media.2007.06.004","volume":"12","author":"BB Avants","year":"2008","unstructured":"Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C.: Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12(1), 26\u201341 (Feb 2008)","journal-title":"Med Image Anal"},{"issue":"3","key":"71_CR3","doi-asserted-by":"publisher","first-page":"2033","DOI":"10.1016\/j.neuroimage.2010.09.025","volume":"54","author":"BB Avants","year":"2011","unstructured":"Avants, B.B., Tustison, N.J., Song, G., Cook, P.A., Klein, A., Gee, J.C.: A reproducible evaluation of ants similarity metric performance in brain image registration. Neuroimage 54(3), 2033\u20132044 (2011)","journal-title":"Neuroimage"},{"issue":"8","key":"71_CR4","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, M.R., Guttag, J., Dalca, A.V.: Voxelmorph: a learning framework for deformable medical image registration. IEEE transactions on medical imaging 38(8), 1788\u20131800 (2019)","journal-title":"IEEE transactions on medical imaging"},{"key":"71_CR5","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1023\/B:VISI.0000043755.93987.aa","volume":"61","author":"MF Beg","year":"2005","unstructured":"Beg, M.F., Miller, M.I., Trouv\u00e9, A., Younes, L.: Computing large deformation metric mappings via geodesic flows of diffeomorphisms. International journal of computer vision 61, 139\u2013157 (2005)","journal-title":"International journal of computer vision"},{"key":"71_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102615","volume":"82","author":"J Chen","year":"2022","unstructured":"Chen, J., Frey, E.C., He, Y., Segars, W.P., Li, Y., Du, Y.: Transmorph: Transformer for unsupervised medical image registration. Medical image analysis 82, 102615 (2022)","journal-title":"Medical image analysis"},{"key":"71_CR7","doi-asserted-by":"crossref","unstructured":"Chen, J., He, Y., Frey, E.C., Li, Y., Du, Y.: Vit-v-net: Vision transformer for unsupervised volumetric medical image registration. arXiv preprint arXiv:2104.06468 (2021)","DOI":"10.1016\/j.media.2022.102615"},{"key":"71_CR8","doi-asserted-by":"publisher","first-page":"226","DOI":"10.1016\/j.media.2019.07.006","volume":"57","author":"A Dalca","year":"2019","unstructured":"Dalca, A., Balakrishnan, G., Guttag, J., Sabuncu, M.R.: Unsupervised learning of probabilistic diffeomorphic registration for images and surfaces. Medical image analysis 57, 226\u2013236 (2019)","journal-title":"Medical image analysis"},{"key":"71_CR9","doi-asserted-by":"crossref","unstructured":"Dalca, A.V., Balakrishnan, G., Guttag, J., Sabuncu, M.R.: Unsupervised learning for fast probabilistic diffeomorphic registration. In: International Conference on Medical Image Computing and Computer-Assisted Intervention. pp. 729\u2013738. Springer (2018)","DOI":"10.1007\/978-3-030-00928-1_82"},{"key":"71_CR10","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1016\/j.media.2018.11.010","volume":"52","author":"BD De Vos","year":"2019","unstructured":"De\u00a0Vos, B.D., Berendsen, F.F., Viergever, M.A., Sokooti, H., Staring, M., I\u0161gum, I.: A deep learning framework for unsupervised affine and deformable image registration. Medical image analysis 52, 128\u2013143 (2019)","journal-title":"Medical image analysis"},{"issue":"9","key":"71_CR11","doi-asserted-by":"publisher","first-page":"2151","DOI":"10.1109\/TMI.2019.2894322","volume":"38","author":"J Duan","year":"2019","unstructured":"Duan, J., Bello, G., Schlemper, J., Bai, W., Dawes, T.J., Biffi, C., de\u00a0Marvao, A., Doumoud, G., O\u2019Regan, D.P., Rueckert, D.: Automatic 3d bi-ventricular segmentation of cardiac images by a shape-refined multi-task deep learning approach. IEEE transactions on medical imaging 38(9), 2151\u20132164 (2019)","journal-title":"IEEE transactions on medical imaging"},{"issue":"10","key":"71_CR12","doi-asserted-by":"publisher","first-page":"5130","DOI":"10.1109\/JBHI.2022.3189696","volume":"26","author":"B Hu","year":"2022","unstructured":"Hu, B., Zhou, S., Xiong, Z., Wu, F.: Recursive decomposition network for deformable image registration. IEEE Journal of Biomedical and Health Informatics 26(10), 5130\u20135141 (2022)","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"71_CR13","doi-asserted-by":"crossref","unstructured":"Jia, X., Bartlett, J., Chen, W., Song, S., Zhang, T., Cheng, X., Lu, W., Qiu, Z., Duan, J.: Fourier-net: Fast image registration with band-limited deformation. In: Proceedings of the AAAI Conference on Artificial Intelligence. vol.\u00a037, pp. 1015\u20131023 (2023)","DOI":"10.1609\/aaai.v37i1.25182"},{"issue":"1","key":"71_CR14","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1109\/TMI.2021.3108881","volume":"41","author":"X Jia","year":"2021","unstructured":"Jia, X., Thorley, A., Chen, W., Qiu, H., Shen, L., Styles, I.B., Chang, H.J., Leonardis, A., De\u00a0Marvao, A., O\u2019Regan, D.P., et\u00a0al.: Learning a model-driven variational network for deformable image registration. IEEE Transactions on Medical Imaging 41(1), 199\u2013212 (2021)","journal-title":"IEEE Transactions on Medical Imaging"},{"key":"71_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102379","volume":"78","author":"M Kang","year":"2022","unstructured":"Kang, M., Hu, X., Huang, W., Scott, M.R., Reyes, M.: Dual-stream pyramid registration network. Medical image analysis 78, 102379 (2022)","journal-title":"Medical image analysis"},{"key":"71_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102036","volume":"71","author":"B Kim","year":"2021","unstructured":"Kim, B., Kim, D.H., Park, S.H., Kim, J., Lee, J.G., Ye, J.C.: Cyclemorph: cycle consistent unsupervised deformable image registration. Medical image analysis 71, 102036 (2021)","journal-title":"Medical image analysis"},{"key":"71_CR17","doi-asserted-by":"crossref","unstructured":"Mok, T.C., Chung, A.C.: Large deformation diffeomorphic image registration with laplacian pyramid networks. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2020: 23rd International Conference, Lima, Peru, October 4\u20138, 2020, Proceedings, Part III 23. pp. 211\u2013221. Springer (2020)","DOI":"10.1007\/978-3-030-59716-0_21"},{"key":"71_CR18","unstructured":"Qiu, H., Qin, C., Schuh, A., Hammernik, K., Rueckert, D.: Learning diffeomorphic and modality-invariant registration using b-splines. In: Medical Imaging with Deep Learning (2021)"},{"issue":"7","key":"71_CR19","doi-asserted-by":"publisher","first-page":"1153","DOI":"10.1109\/TMI.2013.2265603","volume":"32","author":"A Sotiras","year":"2013","unstructured":"Sotiras, A., Davatzikos, C., Paragios, N.: Deformable medical image registration: A survey. IEEE transactions on medical imaging 32(7), 1153\u20131190 (2013)","journal-title":"IEEE transactions on medical imaging"},{"key":"71_CR20","doi-asserted-by":"crossref","unstructured":"Stollnitz, E.J., DeRose, A.D., Salesin, D.H.: Wavelets for computer graphics: a primer. 1. Ieee computer graphics and applications 15(3), 76\u201384 (1995)","DOI":"10.1109\/38.376616"},{"key":"71_CR21","doi-asserted-by":"crossref","unstructured":"Thorley, A., Jia, X., Chang, H.J., Liu, B., Bunting, K., Stoll, V., de\u00a0Marvao, A., O\u2019Regan, D.P., Gkoutos, G., Kotecha, D., et\u00a0al.: Nesterov accelerated admm for fast diffeomorphic image registration. In: Medical Image Computing and Computer Assisted Intervention\u2013MICCAI 2021: 24th International Conference, Strasbourg, France, September 27\u2013October 1, 2021, Proceedings, Part IV 24. pp. 150\u2013160. Springer (2021)","DOI":"10.1007\/978-3-030-87202-1_15"},{"issue":"1","key":"71_CR22","doi-asserted-by":"publisher","first-page":"S61","DOI":"10.1016\/j.neuroimage.2008.10.040","volume":"45","author":"T Vercauteren","year":"2009","unstructured":"Vercauteren, T., Pennec, X., Perchant, A., Ayache, N.: Diffeomorphic demons: Efficient non-parametric image registration. NeuroImage 45(1), S61\u2013S72 (2009)","journal-title":"NeuroImage"},{"key":"71_CR23","doi-asserted-by":"crossref","unstructured":"Wang, H., Ni, Dongand\u00a0Wang, Y.: Modet: Learning deformable image registration via motion decomposition transformer. In: Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2023. pp. 740\u2013749 (2023)","DOI":"10.1007\/978-3-031-43999-5_70"},{"key":"71_CR24","doi-asserted-by":"crossref","unstructured":"Yang, X., Wu, N., Cheng, G., Zhou, Z., David, S.Y., Beitler, J.J., Curran, W.J., Liu, T.: Automated segmentation of the parotid gland based on atlas registration and machine learning: a longitudinal mri study in head-and-neck radiation therapy. International Journal of Radiation Oncology*Biology*Physics 90(5), 1225\u20131233 (2014)","DOI":"10.1016\/j.ijrobp.2014.08.350"},{"key":"71_CR25","unstructured":"Zhang, J.: Inverse-consistent deep networks for unsupervised deformable image registration. arXiv preprint arXiv:1809.03443 (2018)"},{"key":"71_CR26","doi-asserted-by":"crossref","unstructured":"Zhao, S., Dong, Y., Chang, E.I., Xu, Y., et\u00a0al.: Recursive cascaded networks for unsupervised medical image registration. In: Proceedings of the IEEE\/CVF international conference on computer vision. pp. 10600\u201310610 (2019)","DOI":"10.1109\/ICCV.2019.01070"},{"issue":"5","key":"71_CR27","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1109\/JBHI.2019.2951024","volume":"24","author":"S Zhao","year":"2019","unstructured":"Zhao, S., Lau, T., Luo, J., Eric, I., Chang, C., Xu, Y.: Unsupervised 3d end-to-end medical image registration with volume tweening network. IEEE journal of biomedical and health informatics 24(5), 1394\u20131404 (2019)","journal-title":"IEEE journal of biomedical and health informatics"}],"container-title":["Lecture Notes in Computer Science","Medical Image Computing and Computer Assisted Intervention \u2013 MICCAI 2024"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-72069-7_71","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T19:09:52Z","timestamp":1727982592000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-72069-7_71"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031720680","9783031720697"],"references-count":27,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-72069-7_71","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"4 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"MICCAI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Medical Image Computing and Computer-Assisted Intervention","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miccai2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conferences.miccai.org\/2024\/en\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}