{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T04:37:22Z","timestamp":1774413442544,"version":"3.50.1"},"reference-count":59,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018AAA0100704"],"award-info":[{"award-number":["2018AAA0100704"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61932020"],"award-info":[{"award-number":["61932020"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003399","name":"Science and Technology Commission of Shanghai Municipality","doi-asserted-by":"publisher","award":["20ZR1436000"],"award-info":[{"award-number":["20ZR1436000"]}],"id":[{"id":"10.13039\/501100003399","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010226","name":"Department of Education of Guangdong Province","doi-asserted-by":"publisher","award":["2020ZDZX3043"],"award-info":[{"award-number":["2020ZDZX3043"]}],"id":[{"id":"10.13039\/501100010226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenzhen Natural Science Fund","award":["JCYJ20200109140820699"],"award-info":[{"award-number":["JCYJ20200109140820699"]}]},{"name":"Stable Support Plan Program","award":["20200925174052004"],"award-info":[{"award-number":["20200925174052004"]}]},{"name":"\u201cShuguang Program\u201d"},{"DOI":"10.13039\/501100003024","name":"Shanghai Education Development Foundation and Shanghai Municipal Education Commission","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003024","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/tmi.2021.3118223","type":"journal-article","created":{"date-parts":[[2021,10,14]],"date-time":"2021-10-14T00:16:35Z","timestamp":1634170595000},"page":"582-594","source":"Crossref","is-referenced-by-count":46,"title":["Proxy-Bridged Image Reconstruction Network for Anomaly Detection in Medical Images"],"prefix":"10.1109","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8789-4243","authenticated-orcid":false,"given":"Kang","family":"Zhou","sequence":"first","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7027-7513","authenticated-orcid":false,"given":"Jing","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0754-6458","authenticated-orcid":false,"given":"Weixin","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8410-2976","authenticated-orcid":false,"given":"Zhengxin","family":"Li","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7450-1260","authenticated-orcid":false,"given":"Jianlong","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9702-5524","authenticated-orcid":false,"given":"Huazhu","family":"Fu","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research (A*STAR), Institute of High Performance Computing (IHPC), Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1786-6188","authenticated-orcid":false,"given":"Jun","family":"Cheng","sequence":"additional","affiliation":[{"name":"Agency for Science Technology and Research (A*STAR), Institute for Infocomm Research, Singapore"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6281-6505","authenticated-orcid":false,"given":"Jiang","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, Southern University of Science and Technology, Guangdong, Shenzhen, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1626-2040","authenticated-orcid":false,"given":"Shenghua","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Information Science and Technology, ShanghaiTech University, Shanghai, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3101403"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59050-9_12"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32251-9_32"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI45749.2020.9098686"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101713"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2951844"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3000949"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1364\/boe.5.003568"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8512828"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-33391-1_26"},{"key":"ref13","first-page":"1","article-title":"Deep anomaly detection using geometric transformations","volume-title":"Proc. NeurIPS","author":"Golan"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11723-8_16"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098052"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.3156\/jsoft.29.5_177_2"},{"key":"ref17","first-page":"1","article-title":"Unsupervised detection of lesions in brain MRI using constrained adversarial auto-encoders","volume-title":"Proc. Med. Imag. with Deep Learn. (MIDL)","author":"Chen"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20893-6_39"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3046884"},{"key":"ref20","article-title":"Autoencoders that don\u2019t overfit towards the identity","volume-title":"Proc. NeurIPS","author":"Steck"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2003.1238308"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1034\/j.1600-0757.2001.22250102.x"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1111\/bph.13705"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1212\/WNL.46.3.819"},{"key":"ref25","first-page":"7","article-title":"Superpixel masking and inpainting for self-supervised anomaly detection","volume-title":"Proc. 31st Brit. Mach. Vis. Conf.","author":"Li"},{"key":"ref26","first-page":"1","article-title":"Context-encoding variational autoencoder for unsupervised anomaly detection","volume-title":"Proc. Int. Conf. Med. Imag. Deep Learn. (MIDL)","author":"Zimmerer"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101952"},{"issue":"2","key":"ref28","first-page":"8","article-title":"A hybrid approach to brain tumor detection from MRI images using computer vision","volume":"8","author":"Rai","year":"2019","journal-title":"J. Innov. Comput. Sci. Eng."},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-8963-5"},{"key":"ref30","volume-title":"Computer Vision: A Modern Approach","author":"Forsyth","year":"2002"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2004.1315182"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532562"},{"key":"ref33","article-title":"MADGAN: Unsupervised medical anomaly detection GAN using multiple adjacent brain MRI slice reconstruction","author":"Han","year":"2020","journal-title":"arXiv:2007.13559"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.01.010"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI45749.2020.9098374"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2919951"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3040950"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2019.8759442"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_46"},{"key":"ref40","article-title":"Anomaly detection in medical imaging with deep perceptual autoencoders","author":"Shvetsova","year":"2020","journal-title":"arXiv:2006.13265"},{"key":"ref41","first-page":"1","article-title":"Unsupervised lesion detection in brain ct using Bayesian convolutional autoencoders","volume-title":"Proc. Med. Imag. with Deep Learn. (MIDL)","author":"Pawlowski"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.11231"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58565-5_22"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.120"},{"key":"ref48","first-page":"6306","article-title":"Neural discrete representation learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"van den Oord"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00179"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101654"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3043495"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2017.7950500"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101561"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref56","article-title":"Adam: A method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv:1412.6980"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59719-1_2"},{"key":"ref58","volume-title":"Brain Tumor Classification: Classify MRI Images Into Four Classes","author":"Sartaj","year":"2020"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2906319"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/9724621\/09570167.pdf?arnumber=9570167","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T00:01:19Z","timestamp":1705017679000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9570167\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":59,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2021.3118223","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}