{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T21:56:35Z","timestamp":1777758995511,"version":"3.51.4"},"reference-count":23,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"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":["Vis Comput"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1007\/s00371-026-04434-w","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T17:30:38Z","timestamp":1775755838000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic accelerated cardiac CINE MRI reconstruction based on motion compensation"],"prefix":"10.1007","volume":"42","author":[{"given":"Kun","family":"Wu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Pu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alejandro F.","family":"Frangi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Lin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nan","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,9]]},"reference":[{"key":"4434_CR1","doi-asserted-by":"crossref","unstructured":"Zhuang, S., Zhang, H., Liang, D., Liu, H., Gao, Z.: Adaptive sequential bayesian iterative learning for myocardial motion estimation on cardiac image sequences. IEEE Trans. Med. Imag. (2025)","DOI":"10.1109\/TMI.2025.3599487"},{"issue":"6","key":"4434_CR2","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.3174\/ajnr.A5227","volume":"38","author":"LN Tanenbaum","year":"2017","unstructured":"Tanenbaum, L.N., Tsiouris, A.J., Johnson, A.N., Naidich, T.P., DeLano, M.C., Melhem, E.R., Quarterman, P., Parameswaran, S., Shankaranarayanan, A., Goyen, M., et al.: Synthetic MRI for clinical neuroimaging: results of the magnetic resonance image compilation (MAGiC) prospective, multicenter, multireader trial. Am. J. Neuroradiol. 38(6), 1103\u20131110 (2017)","journal-title":"Am. J. Neuroradiol."},{"issue":"8","key":"4434_CR3","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1002\/cpa.20124","volume":"59","author":"EJ Candes","year":"2006","unstructured":"Candes, E.J., Romberg, J.K., Tao, T.: Stable signal recovery from incomplete and inaccurate measurements. Commun. Pure Appl. Math.: A J. Issued Courant Instit. Math. Sci. 59(8), 1207\u20131223 (2006)","journal-title":"Commun. Pure Appl. Math.: A J. Issued Courant Instit. Math. Sci."},{"issue":"4","key":"4434_CR4","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho, D.L.: Compressed sensing. IEEE Trans. Inf. Theory 52(4), 1289\u20131306 (2006)","journal-title":"IEEE Trans. Inf. Theory"},{"key":"4434_CR5","doi-asserted-by":"crossref","unstructured":"Li, X., Meng, M., Huang, Z., Bi, L., Delamare, E., Feng, D., Sheng, B., Kim, J.: 3dpx: Progressive 2d-to-3d oral image reconstruction with hybrid mlp-cnn networks. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 25\u201334 (2024). Springer","DOI":"10.1007\/978-3-031-72104-5_3"},{"issue":"1","key":"4434_CR6","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1109\/TMI.2023.3289859","volume":"43","author":"J Li","year":"2023","unstructured":"Li, J., Zhang, P., Wang, T., Zhu, L., Liu, R., Yang, X., Wang, K., Shen, D., Sheng, B.: Dsmt-net: dual self-supervised multi-operator transformation for multi-source endoscopic ultrasound diagnosis. IEEE Trans. Med. Imag. 43(1), 64\u201375 (2023)","journal-title":"IEEE Trans. Med. Imag."},{"issue":"11","key":"4434_CR7","doi-asserted-by":"crossref","first-page":"13489","DOI":"10.1109\/TPAMI.2023.3289667","volume":"45","author":"Z Chen","year":"2023","unstructured":"Chen, Z., Qiu, G., Li, P., Zhu, L., Yang, X., Sheng, B.: Mngnas: distilling adaptive combination of multiple searched networks for one-shot neural architecture search. IEEE Trans. Pattern Anal. Mach. Intell. 45(11), 13489\u201313508 (2023)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"2","key":"4434_CR8","doi-asserted-by":"publisher","first-page":"320","DOI":"10.1007\/s11390-024-3419-7","volume":"39","author":"Y Jung","year":"2024","unstructured":"Jung, Y., Kong, J., Sheng, B., Kim, J.: A transfer function design for medical volume data using a knowledge database based on deep image and primitive intensity profile features retrieval. J. Comput. Sci. Technol. 39(2), 320\u2013335 (2024)","journal-title":"J. Comput. Sci. Technol."},{"issue":"2","key":"4434_CR9","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1038\/s41591-023-02702-z","volume":"30","author":"L Dai","year":"2024","unstructured":"Dai, L., Sheng, B., Chen, T., Wu, Q., Liu, R., Cai, C., Wu, L., Yang, D., Hamzah, H., Liu, Y., et al.: A deep learning system for predicting time to progression of diabetic retinopathy. Nat. Med. 30(2), 584\u2013594 (2024)","journal-title":"Nat. Med."},{"key":"4434_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2024.102919","volume":"154","author":"J Li","year":"2024","unstructured":"Li, J., Zhang, P., Yang, X., Zhu, L., Wang, T., Zhang, P., Liu, R., Sheng, B., Wang, K.: Ssm-net: Semi-supervised multi-task network for joint lesion segmentation and classification from pancreatic eus images. Artif. Intell. Med. 154, 102919 (2024)","journal-title":"Artif. Intell. Med."},{"issue":"5","key":"4434_CR11","doi-asserted-by":"publisher","first-page":"1273","DOI":"10.1002\/mrm.20656","volume":"54","author":"P Batchelor","year":"2005","unstructured":"Batchelor, P., Atkinson, D., Irarrazaval, P., Hill, D., Hajnal, J., Larkman, D.: Matrix description of general motion correction applied to multishot images. Magn. Resonance Med.: An Off. J. Int. Soc. Magnetic Resonance Med. 54(5), 1273\u20131280 (2005)","journal-title":"Magn. Resonance Med.: An Off. J. Int. Soc. Magnetic Resonance Med."},{"key":"4434_CR12","doi-asserted-by":"crossref","unstructured":"Bilen, \u00c7., Selesnick, I., Wang, Y., Otazo, R., Sodickson, D.K.: A motion compensating prior for dynamic MRI reconstruction using combination of compressed sensing and parallel imaging. In: 2011 IEEE Signal Processing in Medicine and Biology Symposium (SPMB), pp. 1\u20136 (2011). IEEE","DOI":"10.1109\/SPMB.2011.6120105"},{"issue":"1","key":"4434_CR13","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1109\/TMI.2020.3029205","volume":"40","author":"H Qi","year":"2020","unstructured":"Qi, H., Fuin, N., Cruz, G., Pan, J., Kuestner, T., Bustin, A., Botnar, R.M., Prieto, C.: Non-rigid respiratory motion estimation of whole-heart coronary MR images using unsupervised deep learning. IEEE Trans. Med. Imag. 40(1), 444\u2013454 (2020)","journal-title":"IEEE Trans. Med. Imag."},{"key":"4434_CR14","doi-asserted-by":"crossref","unstructured":"Seegoolam, G., Schlemper, J., Qin, C., Price, A., Hajnal, J., Rueckert, D.: Exploiting motion for deep learning reconstruction of extremely-undersampled dynamic mri. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 704\u2013712 (2019). Springer","DOI":"10.1007\/978-3-030-32251-9_77"},{"key":"4434_CR15","unstructured":"Feng, J., Feng, R., Wu, Q., Zhang, Z., Zhang, Y., Wei, H.: Spatiotemporal implicit neural representation for unsupervised dynamic MRI reconstruction. arXiv preprint arXiv:2301.00127 (2022)"},{"key":"4434_CR16","doi-asserted-by":"crossref","unstructured":"Pan, J., Rueckert, D., K\u00fcstner, T., Hammernik, K.: Efficient image registration network for non-rigid cardiac motion estimation. In: International Workshop on Machine Learning for Medical Image Reconstruction, pp. 14\u201324 (2021). Springer","DOI":"10.1007\/978-3-030-88552-6_2"},{"key":"4434_CR17","doi-asserted-by":"crossref","unstructured":"Hammernik, K., Pan, J., Rueckert, D., K\u00fcstner, T.: Motion-guided physics-based learning for cardiac MRI reconstruction. In: 2021 55th Asilomar Conference on Signals, Systems, and Computers, pp. 900\u2013907 (2021). IEEE","DOI":"10.1109\/IEEECONF53345.2021.9723134"},{"key":"4434_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2024.106560","volume":"96","author":"K Wu","year":"2024","unstructured":"Wu, K., Xia, Y., Ravikumar, N., Frangi, A.F.: Compressed sensing using a deep adaptive perceptual generative adversarial network for MRI reconstruction from undersampled k-space data. Biomed. Signal Process. Control 96, 106560 (2024)","journal-title":"Biomed. Signal Process. Control"},{"key":"4434_CR19","doi-asserted-by":"crossref","unstructured":"Caballero, J., Ledig, C., Aitken, A., Acosta, A., Totz, J., Wang, Z., Shi, W.: Real-time video super-resolution with spatio-temporal networks and motion compensation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4778\u20134787 (2017)","DOI":"10.1109\/CVPR.2017.304"},{"issue":"1","key":"4434_CR20","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1186\/s12968-016-0227-4","volume":"18","author":"SE Petersen","year":"2016","unstructured":"Petersen, S.E., Matthews, P.M., Francis, J.M., Robson, M.D., Zemrak, F., Boubertakh, R., Young, A.A., Hudson, S., Weale, P., Garratt, S., et al.: Uk biobank\u2019s cardiovascular magnetic resonance protocol. J. Cardiovasc. Magn. Reson. 18(1), 8 (2016)","journal-title":"J. Cardiovasc. Magn. Reson."},{"issue":"3","key":"4434_CR21","doi-asserted-by":"publisher","first-page":"1125","DOI":"10.1002\/mrm.25240","volume":"73","author":"R Otazo","year":"2015","unstructured":"Otazo, R., Candes, E., Sodickson, D.K.: Low-rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components. Magn. Reson. Med. 73(3), 1125\u20131136 (2015)","journal-title":"Magn. Reson. Med."},{"issue":"6","key":"4434_CR22","doi-asserted-by":"publisher","first-page":"3274","DOI":"10.1002\/mrm.28917","volume":"86","author":"C Qin","year":"2021","unstructured":"Qin, C., Duan, J., Hammernik, K., Schlemper, J., K\u00fcstner, T., Botnar, R., Prieto, C., Price, A.N., Hajnal, J.V., Rueckert, D.: Complementary time-frequency domain networks for dynamic parallel MR image reconstruction. Magn. Reson. Med. 86(6), 3274\u20133291 (2021)","journal-title":"Magn. Reson. Med."},{"key":"4434_CR23","doi-asserted-by":"crossref","unstructured":"Pan, J., Rueckert, D., K\u00fcstner, T., Hammernik, K.: Learning-based and unrolled motion-compensated reconstruction for cardiac MR cine imaging. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 686\u2013696 (2022). Springer","DOI":"10.1007\/978-3-031-16446-0_65"}],"updated-by":[{"DOI":"10.1007\/s00371-026-04500-3","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T00:00:00Z","timestamp":1776816000000}}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04434-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-026-04434-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-026-04434-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T13:18:06Z","timestamp":1777468686000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-026-04434-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":23,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["4434"],"URL":"https:\/\/doi.org\/10.1007\/s00371-026-04434-w","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"4 February 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 April 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 April 2026","order":5,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Update","order":6,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The original online version of this article was revised: The open ethical statement was missing","order":7,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2026","order":8,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":9,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":10,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s00371-026-04500-3","URL":"https:\/\/doi.org\/10.1007\/s00371-026-04500-3","order":11,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This research study was conducted retrospectively using human subject data made available in open access by UK BioBank (access application 11350). Ethical approval was not required as confirmed by the license attached with the open access data.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical statement"}},{"value":"The authors declare no Conflict of interest.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"247"}}