{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:06:57Z","timestamp":1778256417848,"version":"3.51.4"},"reference-count":51,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Hong Kong Research Grants Council (RGC) General Research","award":["14220622"],"award-info":[{"award-number":["14220622"]}]},{"name":"Hong Kong Research Grants Council (RGC) General Research","award":["14204321"],"award-info":[{"award-number":["14204321"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1109\/jbhi.2025.3525854","type":"journal-article","created":{"date-parts":[[2025,1,6]],"date-time":"2025-01-06T19:40:02Z","timestamp":1736192402000},"page":"3159-3170","source":"Crossref","is-referenced-by-count":4,"title":["Progressive Distillation With Optimal Transport for Federated Incomplete Multi-Modal Learning of Brain Tumor Segmentation"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5737-5653","authenticated-orcid":false,"given":"Qiushi","family":"Yang","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5563-7282","authenticated-orcid":false,"given":"Meilu","family":"Zhu","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, City University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter Y. M.","family":"Woo","sequence":"additional","affiliation":[{"name":"Division of Neurosurgery, Department of Surgery, Hospital Authority, Prince of Wales Hospital, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9542-6666","authenticated-orcid":false,"given":"Leanne Lai-Hang","family":"Chan","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, City University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0853-6948","authenticated-orcid":false,"given":"Yixuan","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.004"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59719-1_47"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3034995"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-46643-5_28"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.metrad.2023.100004"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.2973510"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72087-2_39"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_50"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_54"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3070752"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-78191-0_25"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_9"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_75"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87234-2_39"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3175478"},{"key":"ref16","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"McMahan","year":"2017"},{"key":"ref17","article-title":"Fedbn: Federated learning on non-IID features via local batch normalization","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Li","year":"2021"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00821"},{"key":"ref19","first-page":"429","article-title":"Federated optimization in heterogeneous networks","volume-title":"Proc. Mach. Learn. Syst.","author":"Li","year":"2020"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00438"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3192483"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00431-6"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00984"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16960"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00993"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00987"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00503"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00522"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1088\/1751-8121\/ab5d4d"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01129"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00261"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2022.3217388"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2945521"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01524"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00394"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_11"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20819"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI45749.2020.9098449"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3023609"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.5555\/3045118.3045167"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00653"},{"key":"ref42","article-title":"The dynamic hungarian algorithm for the assignment problem with changing costs","author":"Mills-Tettey","year":"2007"},{"key":"ref43","article-title":"Federated learning with matched averaging","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Wang","year":"2020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01139"},{"key":"ref45","article-title":"Personalized federated learning with feature alignment and classifier collaboration","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu","year":"2023"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CAC63892.2024.10865360"},{"key":"ref47","first-page":"321","article-title":"Representation disentanglement for multi-modal mr analysis","volume-title":"Proc. Inf. Process. Med. Imaging, 27th Int. Conf.","author":"Ouyang","year":"2021"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32245-8_33"},{"key":"ref49","article-title":"SNIP: Single-shot network pruning based on connection sensitivity","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Lee","year":"2019"},{"key":"ref50","first-page":"6377","article-title":"Pruning neural networks without any data by iteratively conserving synaptic flow","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Tanaka","year":"2020"},{"key":"ref51","article-title":"Picking winning tickets before training by preserving gradient flow","author":"Wang","year":"2020"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221020\/10989059\/10824938.pdf?arnumber=10824938","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T04:22:00Z","timestamp":1746591720000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10824938\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":51,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2025.3525854","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}