{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T06:22:15Z","timestamp":1768890135486,"version":"3.49.0"},"reference-count":67,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T00:00:00Z","timestamp":1761955200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62306254"],"award-info":[{"award-number":["62306254"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Joint Research Scheme (JRS) through the National Natural Science Foundation of China (NSFC) and Research Grants Council (RGC) of Hong Kong","award":["N_HKUST654\/24"],"award-info":[{"award-number":["N_HKUST654\/24"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1109\/tnnls.2025.3590956","type":"journal-article","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T17:45:03Z","timestamp":1754588703000},"page":"19718-19732","source":"Crossref","is-referenced-by-count":1,"title":["Enhancing Domain Generalization in Medical Image Segmentation With Global and Local Prompts"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6220-0540","authenticated-orcid":false,"given":"Chuang","family":"Zhao","sequence":"first","affiliation":[{"name":"Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, SAR, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1105-8083","authenticated-orcid":false,"given":"Xiaomeng","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, SAR, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3193146"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3296652"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3238381"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3383467"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103164"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3332003"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87196-3_29"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2995319"},{"key":"ref9","first-page":"6438","article-title":"Manifold mixup: Better representations by interpolating hidden states","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Verma"},{"key":"ref10","article-title":"Domain generalization with mixstyle","volume-title":"Proc. ICLR","author":"Zhou"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00786"},{"key":"ref12","article-title":"Aggregation of disentanglement: Reconsidering domain variations in domain generalization","author":"Zhang","year":"2023","journal-title":"arXiv:2302.02350"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00342"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19775-8_30"},{"key":"ref15","article-title":"Prompt vision transformer for domain generalization","volume-title":"CoRR","volume":"abs\/2208.08914","author":"Zheng"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01892"},{"key":"ref17","article-title":"Vision transformer adapter for dense predictions","volume-title":"Proc. ICLR","author":"Chen"},{"key":"ref18","article-title":"LoRA: Low-rank adaptation of large language models","volume-title":"Proc. ICLR","author":"Hu"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43990-2_24"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102914"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2021.3117407"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2973595"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102904"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3241919"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16449-1_67"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.2992393"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43901-8_9"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/abfbf4"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3274760"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2025.3548070"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00787"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3195549"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3178128"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2024.3454689"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_15"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3210133"},{"key":"ref38","first-page":"3251","article-title":"MetaPrompting: Learning to learn better prompts","volume-title":"Proc. COLING","author":"Hou"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-47401-9_3"},{"key":"ref40","article-title":"Exploring visual prompts for whole slide image classification with multiple instance learning","author":"Lin","year":"2023","journal-title":"arXiv:2303.13122"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.8"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acllong.353"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.acl-short.1"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00390"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.243"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3560815"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2102.04306"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-021-10004-4"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01109"},{"key":"ref51","first-page":"10369","article-title":"Gaussian process prior variational autoencoders","volume-title":"Proc. NeurIPS","volume":"31","author":"Casale"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2017.03.010"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3090082"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59713-9_46"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68107-4_19"},{"key":"ref57","article-title":"Domain generalization for medical imaging classification with linear-dependency regularization","volume-title":"Proc. NeurIPS","author":"Li"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00107"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.107132"},{"key":"ref60","article-title":"Robust and generalizable visual representation learning via random convolutions","volume-title":"Proc. ICLR","author":"Xu"},{"key":"ref61","article-title":"Uncertainty modeling for out-of-distribution generalization","volume-title":"Proc. ICLR","author":"Li"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00105"},{"key":"ref64","article-title":"Reliability benchmarks for image segmentation","volume-title":"Proc. NeurIPS","author":"Buchanan"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"issue":"5","key":"ref66","first-page":"73","article-title":"Visualizing time-dependent data using dynamic t-SNE","volume-title":"Proc. Eurograph. Conf. Vis.","volume":"2","author":"Rauber"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19827-4_41"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5962385\/11220834\/11119233.pdf?arnumber=11119233","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T18:41:35Z","timestamp":1765219295000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11119233\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11]]},"references-count":67,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2025.3590956","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11]]}}}