{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,18]],"date-time":"2026-05-18T10:12:30Z","timestamp":1779099150775,"version":"3.51.4"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T00:00:00Z","timestamp":1756684800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100007432","name":"National Institute for Health and Care Research for the Manchester Biomedical Research Centre","doi-asserted-by":"publisher","award":["NIHR203308"],"award-info":[{"award-number":["NIHR203308"]}],"id":[{"id":"10.13039\/501100007432","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Engineering and Physical Sciences Research Council (EPSRC) for the INSILICO project","award":["EP\/Y030494\/1"],"award-info":[{"award-number":["EP\/Y030494\/1"]}]},{"name":"Royal Academy of Engineering for the INSILEX initiative","award":["CiET1819\/19"],"award-info":[{"award-number":["CiET1819\/19"]}]},{"name":"Medical Research Council (MRC) and Innovate UK for the UK Centre of Excellence for In-Silico Regulatory Science and Innovation","award":["10139527"],"award-info":[{"award-number":["10139527"]}]},{"name":"British Heart Foundation (BHF) for the Manchester Centre for Research Excellence","award":["RE\/24\/130017"],"award-info":[{"award-number":["RE\/24\/130017"]}]},{"name":"Cancer Research UK (CRUK) for RadNet","award":["C1994\/A28701"],"award-info":[{"award-number":["C1994\/A28701"]}]},{"DOI":"10.13039\/501100018984","name":"start-up fund provided by the University of Glasgow","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100018984","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1109\/tmi.2024.3435000","type":"journal-article","created":{"date-parts":[[2024,8,5]],"date-time":"2024-08-05T13:41:59Z","timestamp":1722865319000},"page":"3515-3528","source":"Crossref","is-referenced-by-count":5,"title":["SegMorph: Concurrent Motion Estimation and Segmentation for Cardiac MRI Sequences"],"prefix":"10.1109","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7505-3997","authenticated-orcid":false,"given":"Ning","family":"Bi","sequence":"first","affiliation":[{"name":"Centre for Computational Imaging and Simulation Technologies in Biomedicine (CISTIB) and the School of Computing, University of Leeds, Leeds, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6011-2333","authenticated-orcid":false,"given":"Arezoo","family":"Zakeri","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging, and Data Sciences, School of Health Sciences, Faculty of Biology, Medicine, andHealth, Christabel Pankhurst Institute, The University of Manchester, Manchester, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5952-566X","authenticated-orcid":false,"given":"Yan","family":"Xia","sequence":"additional","affiliation":[{"name":"CISTIB, School of Computing, University of Leeds, Leeds, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nina","family":"Cheng","sequence":"additional","affiliation":[{"name":"CISTIB, School of Computing, University of Leeds, Leeds, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2675-528X","authenticated-orcid":false,"given":"Alejandro F.","family":"Frangi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Faculty of Science and Engineering, Christabel Pankhurst Institute and the Division of Informatics, Imaging and Data Science, Faculty of Biology, Medicine, and Health, The University of Manchester, Manchester, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5135-4800","authenticated-orcid":false,"given":"Ali","family":"Gooya","sequence":"additional","affiliation":[{"name":"School of Computing Science, University of Glasgow, Glasgow, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"81","volume-title":"Respiratory motion modelling using cGANs Medical Image Computing and Computer Assisted Intervention\u2014MICCAI, \u201d 2018 21st International Conference","author":"Giger"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102260"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.21037\/qims-19-1058"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-1009-y"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1111\/echo.14086"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26534"},{"key":"ref7","first-page":"586","volume-title":"Recurrent neural networks for aortic image sequence segmentation with sparse annotations \u201d Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2018: 21st International Conference","author":"Bai"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3056531"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.07.006"},{"key":"ref10","first-page":"472","volume-title":"Joint learning of motion estimation and segmentation for cardiac MR image sequences\u201d Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2018: 21st International Conference","author":"Qin"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_47"},{"key":"ref12","first-page":"310","volume-title":"U-ReSNet: Ultimate coupling of registration and segmentation with deep nets \u201d Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2019: 22nd International Conference","author":"Estienne"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10334-015-0521-4"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2014.10.004"},{"key":"ref15","article-title":"A fully convolutional neural network for cardiac segmentation in short-axis MRI","author":"Vu Tran","year":"2016","journal-title":"arXiv:1604.00494"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-018-0471-x"},{"key":"ref17","first-page":"234","volume-title":"U-Net: Convolutional networks for biomedical image segmentation\u201d Medical Image Computing and Computer-Assisted Intervention\u2014MICCAI 2015: 18th International Conference,","author":"Ronneberger"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"ref19","first-page":"523","volume-title":"Learning shape priors for robust cardiac MR segmentation from multi-view \u201d in images  Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2019: 22nd International Conference","author":"Chen"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2018.2865450"},{"key":"ref21","first-page":"613","volume-title":"Left ventricle segmentation via optical-flow-net from short-axis cine MRI: Preserving the temporal coherence of cardiac motion \u201d in Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2018: 21st International Conference","author":"Yan"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/JTEHM.2019.2900628"},{"key":"ref23","first-page":"802","article-title":"Convolutional LSTM network: A machine learning approach for precipitation nowcasting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Shi"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-75525-4"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2002.804441"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/S1361-8415(01)00050-0"},{"key":"ref27","doi-asserted-by":"crossref","DOI":"10.1016\/j.media.2022.102678","article-title":"DragNet: Learning-based deformable registration for realistic cardiac MR sequence generation from a single frame","volume":"83","author":"Zakeri","year":"2023","journal-title":"Med. Image Anal."},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.04.114"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000043755.93987.aa"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.09.025"},{"key":"ref31","first-page":"300","volume-title":"Deformable image registration based on similarity-steered CNN regression \u201d in Medical Image Computing and Computer Assisted Intervention\u2014MICCAI 2017: 20th International Conference","author":"Cao"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.03.006"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2953788"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00964"},{"key":"ref35","first-page":"2017","article-title":"Spatial transformer networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Jaderberg"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2897538"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.07.006"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_12"},{"key":"ref39","first-page":"3581","article-title":"Semi-supervised learning with deep generative models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"27","author":"Kingma"},{"key":"ref40","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"Bai","year":"2018","journal-title":"arXiv:1803.01271"},{"key":"ref41","first-page":"2980","article-title":"A recurrent latent variable model for sequential data","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Chung"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/MMBIA.2001.991698"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2005.11.044"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-15705-9_60"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1312.6114"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00022"},{"issue":"6","key":"ref47","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","volume":"5","author":"Kingma"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-016-0227-4"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1186\/1532-429X-15-46"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1186\/1532-429X-13-36"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1093\/ehjci\/jew042"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1148\/ryct.2020190032"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102682"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1093\/ehjci\/jev006"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2015.05.006"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.2307\/1932409.JSTOR1932409"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2008.2004420"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1186\/s12968-018-0448-9"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/42\/11165775\/10623527.pdf?arnumber=10623527","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T17:31:17Z","timestamp":1758130277000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10623527\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":59,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2024.3435000","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9]]}}}