{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T23:19:51Z","timestamp":1778195991657,"version":"3.51.4"},"reference-count":69,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"7","license":[{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,7,1]],"date-time":"2024-07-01T00:00:00Z","timestamp":1719792000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Science and Technology Major Project of China","award":["2022ZD0117801"],"award-info":[{"award-number":["2022ZD0117801"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U23B2054"],"award-info":[{"award-number":["U23B2054"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62276263"],"award-info":[{"award-number":["62276263"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62350068"],"award-info":[{"award-number":["62350068"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Clinical Research Project","award":["2022LC2204"],"award-info":[{"award-number":["2022LC2204"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2024,7]]},"DOI":"10.1109\/jbhi.2024.3385098","type":"journal-article","created":{"date-parts":[[2024,4,9]],"date-time":"2024-04-09T19:39:59Z","timestamp":1712691599000},"page":"4170-4183","source":"Crossref","is-referenced-by-count":10,"title":["Exploring Generalizable Distillation for Efficient Medical Image Segmentation"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9772-5707","authenticated-orcid":false,"given":"Xingqun","family":"Qi","sequence":"first","affiliation":[{"name":"AIS, The Hong Kong University of Science and Technology, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-7243-0901","authenticated-orcid":false,"given":"Zhuojie","family":"Wu","sequence":"additional","affiliation":[{"name":"School of EECS, The University of Queensland, Brisbane, QLD, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6945-3513","authenticated-orcid":false,"given":"Wenxuan","family":"Zou","sequence":"additional","affiliation":[{"name":"School of BCME, Beihang University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0126-1726","authenticated-orcid":false,"given":"Min","family":"Ren","sequence":"additional","affiliation":[{"name":"School of AI, Beijing Normal University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6078-4092","authenticated-orcid":false,"given":"Yifan","family":"Gao","sequence":"additional","affiliation":[{"name":"School of MIS, Guangzhou University, Guangzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9506-7643","authenticated-orcid":false,"given":"Muyi","family":"Sun","sequence":"additional","affiliation":[{"name":"School of AI, Beijing University of Posts and Telecommunications, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4047-3526","authenticated-orcid":false,"given":"Shanghang","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of CS, Peking University, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2131-1671","authenticated-orcid":false,"given":"Caifeng","family":"Shan","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology and School of Intelligence Science and Technology, Nanjing University, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4029-9935","authenticated-orcid":false,"given":"Zhenan","family":"Sun","sequence":"additional","affiliation":[{"name":"CRIPAC, MAIS, CASIA, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2959609"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/3DV.2016.79"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2019.2963873"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87196-3_51"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/455"},{"key":"ref7","first-page":"38087","article-title":"Smoothquant: Accurate and efficient post-training quantization for large language models","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Xiao","year":"2023"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3164285"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00447"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01467"},{"key":"ref11","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref12","first-page":"1","article-title":"Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zagoruyko","year":"2017"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.754"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3001940"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58571-6_21"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM52615.2021.9669551"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_51"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-49409-8_43"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01375"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01135"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref22","article-title":"Representation learning with contrastive predictive coding","author":"Oord","year":"2018"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref24","article-title":"Contrastive representation distillation","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Tian","year":"2019"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01387"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59719-1_36"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2020.3028180"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87193-2_22"},{"key":"ref29","first-page":"2189","article-title":"Environment inference for invariant learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Creager","year":"2021"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101950"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102680"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2004.825627"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/42.845178"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2012.2205687"},{"key":"ref35","article-title":"Are GANs created equal? A large-scale study","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Lucic","year":"2018"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref37","article-title":"Enet: A deep neural network architecture for real-time semantic segmentation","author":"Paszke","year":"2016"},{"key":"ref38","first-page":"21128","article-title":"RSA: Reducing semantic shift from aggressive augmentations for self-supervised learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Bai","year":"2022"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2979745"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TCSII.2022.3181132"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.03.046"},{"key":"ref42","first-page":"322","article-title":"Fine-grained analysis of optimization and generalization for overparameterized two-layer neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Arora","year":"2019"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00718"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3246102"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i3.20193"},{"key":"ref46","article-title":"Is deeper better only when shallow is good?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Malach","year":"2019"},{"key":"ref47","first-page":"26989","article-title":"The staircase property: How hierarchical structure can guide deep learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Abbe","year":"2021"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19806-9_1"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00968"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01523"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2015.02.007"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-37734-2_37"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1802.00368"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3224459"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3166230"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2023.3273528"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3224067"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3210133"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref60","article-title":"Transunet: Transformers make strong encoders for medical image segmentation","author":"Chen","year":"2021"},{"key":"ref61","article-title":"Deep-significance: Easy and meaningful signifcance testing in the age of neural networks","volume-title":"Proc. ML Eval. Standards Workshop 10th Int. Conf. Learn. Representations","author":"Ulmer","year":"2022"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_7"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2022.837646"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2023.3237183"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/mce.2022.3181759"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3098355"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-02437-9"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/tmm.2023.3263549"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1145\/3474085.3475434"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/10582272\/10491241.pdf?arnumber=10491241","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T04:06:08Z","timestamp":1720065968000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10491241\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7]]},"references-count":69,"journal-issue":{"issue":"7"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2024.3385098","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7]]}}}