{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T02:10:57Z","timestamp":1768443057911,"version":"3.49.0"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T00:00:00Z","timestamp":1717200000000},"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":["62071049"],"award-info":[{"award-number":["62071049"]}],"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":["61801026"],"award-info":[{"award-number":["61801026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Beijing Municipal Natural Science Foundation"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1109\/jbhi.2024.3365784","type":"journal-article","created":{"date-parts":[[2024,2,13]],"date-time":"2024-02-13T23:52:17Z","timestamp":1707868337000},"page":"3571-3582","source":"Crossref","is-referenced-by-count":8,"title":["Adaptive Knowledge Distillation for High-Quality Unsupervised MRI Reconstruction With Model-Driven Priors"],"prefix":"10.1109","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7980-4957","authenticated-orcid":false,"given":"Zhengliang","family":"Wu","sequence":"first","affiliation":[{"name":"School of Computer Science &amp; Technology, Beijing Institute of Technology, Beijing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1570-277X","authenticated-orcid":false,"given":"Xuesong","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science &amp; Technology, Beijing Institute of Technology, Beijing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.26599\/bdma.2018.9020001"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21391"},{"issue":"2","key":"ref3","first-page":"224","article-title":"AI-based reconstruction for fast MRIA systematic review and meta-analysis","volume-title":"Proc. IEEE","volume":"110","author":"Chen","year":"2022"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102579"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2006.871582"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2007.914728"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-17989-2"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/tit.2008.920190"},{"issue":"2","key":"ref9","first-page":"203","article-title":"Automated parameter selection for accelerated MRI reconstruction via low-rank modeling of local k-space neighborhoods","volume-title":"Zeitschrift fr Medizinische Physik","volume":"33","author":"Ilicak","year":"2023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1561\/2200000016"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2011.06.011"},{"key":"ref12","article-title":"fastMRI: An open dataset and benchmarks for accelerated MRI","volume":"abs\/1811.08839","author":"Zbontar","year":"2018","journal-title":"CoRR"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1002\/nbm.4224"},{"key":"ref14","article-title":"Zero-shot self-supervised learning for MRI reconstruction","volume-title":"Proc. 10th Int. Conf. Learn. Representations","author":"Yaman","year":"2022"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2016.7493320"},{"key":"ref16","first-page":"10","article-title":"Deep ADMM-net for compressive sensing MRI","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Yang","year":"2016"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2022.3220757"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2023.3331413"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2019.2931092"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/access.2018.2881492"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.11.107"},{"key":"ref22","first-page":"9446","article-title":"Deep image prior","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Ulyanov","year":"2018"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/tci.2020.3018562"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102047"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2022.3147426"},{"key":"ref26","article-title":"Adaptive diffusion priors for accelerated MRI reconstruction","volume-title":"Med. Image Anal.","volume":"88","author":"Gngr","year":"2023"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.00975"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.5555\/3524938.3525087"},{"key":"ref29","first-page":"15745","article-title":"Exploring simple siamese representation learning","volume-title":"Proc. IEEE Conf. Comput. Vis. Pattern Recognit.","author":"Chen","year":"2021"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28378"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.3390\/bioengineering9110650"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2022.3213669"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43999-5_47"},{"key":"ref34","article-title":"Distilling the knowledge in a neural network","volume":"abs\/1503.02531","author":"Hinton","year":"2015","journal-title":"CoRR"},{"key":"ref35","first-page":"1607","article-title":"Born again neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Furlanello","year":"2018"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015628"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00454"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-021-01453-z"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20890-5_34"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2022.05.061"},{"key":"ref41","first-page":"515","article-title":"KD-MRI: A knowledge distillation framework for image reconstruction and image restoration in MRI workflow","volume-title":"Proc. Int. Conf. Med. Imag. Deep Learn.","author":"Murugesan","year":"2020"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098135"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682450"},{"key":"ref44","first-page":"12345","article-title":"Agree to disagree: Adaptive ensemble knowledge distillation in gradient space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Du","year":"2020"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/icassp40776.2020.9054698"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/icassp43922.2022.9747534"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58529-7_39"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2760978"},{"key":"ref49","article-title":"Learning confidence for out-of-distribution detection in neural networks","volume":"abs\/1802.04865","author":"DeVries","year":"2018","journal-title":"CoRR"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-023-10562-9"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.24751"},{"key":"ref52","article-title":"XPDNet for MRI reconstruction: An application to the fastMRI 2020 brain challenge","volume":"abs\/2010.07290","author":"Ramzi","year":"2020","journal-title":"CoRR"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1002\/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/tmi.2018.2865356"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.26977"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59713-9_7"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553380"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1145\/3472291"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.28546"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-33391-1_13"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33415-3_32"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2016.03.018"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/10550931\/10433659.pdf?arnumber=10433659","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,11]],"date-time":"2024-12-11T01:55:52Z","timestamp":1733882152000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10433659\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6]]},"references-count":62,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2024.3365784","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,6]]}}}