{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T05:23:34Z","timestamp":1779254614740,"version":"3.51.4"},"reference-count":119,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100005979","name":"Lustgarten Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005979","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Patrick J. McGovern Foundation Award"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Pattern Anal. Mach. Intell."],"published-print":{"date-parts":[[2024,9]]},"DOI":"10.1109\/tpami.2024.3382009","type":"journal-article","created":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T20:16:12Z","timestamp":1711484172000},"page":"6070-6081","source":"Crossref","is-referenced-by-count":11,"title":["Exploiting Structural Consistency of Chest Anatomy for Unsupervised Anomaly Detection in Radiography Images"],"prefix":"10.1109","volume":"46","author":[{"given":"Tiange","family":"Xiang","sequence":"first","affiliation":[{"name":"School of Computer Science, University of Sydney, Camperdown, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2451-4589","authenticated-orcid":false,"given":"Yixiao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1398-9965","authenticated-orcid":false,"given":"Yongyi","family":"Lu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan","family":"Yuille","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8492-9711","authenticated-orcid":false,"given":"Chaoyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science, University of Sydney, Camperdown, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3706-8896","authenticated-orcid":false,"given":"Weidong","family":"Cai","sequence":"additional","affiliation":[{"name":"School of Computer Science, University of Sydney, Camperdown, NSW, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3154-9851","authenticated-orcid":false,"given":"Zongwei","family":"Zhou","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01353"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3060634"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_14"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-09108-7_12"},{"key":"ref5","article-title":"Towards annotation-efficient deep learning for computer-aided diagnosis","author":"Zhou","year":"2021"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/jor.22948"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2529500"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00937-3_84"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-018-0143-2"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_66"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-60548-3_9"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32251-9_42"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101952"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/s13244-016-0534-1"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4899-7993-3_80719-1"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.5120\/13715-1478"},{"key":"ref17","first-page":"582","article-title":"Support vector method for novelty detection","volume-title":"Proc. 12th Int. Conf. Neural Inf. Process. Syst.","author":"Sch\u00f6lkopf"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995524"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995434"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.111"},{"key":"ref21","first-page":"4393","article-title":"Deep one-class classification","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ruff"},{"key":"ref22","article-title":"Deep autoencoding Gaussian mixture model for unsupervised anomaly detection","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Zong"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2016.11.001"},{"key":"ref24","article-title":"A baseline for detecting misclassified and out-of-distribution examples in neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hendrycks"},{"key":"ref25","article-title":"Training confidence-calibrated classifiers for detecting out-of-distribution samples","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Lee"},{"key":"ref26","article-title":"Enhancing the reliability of out-of-distribution image detection in neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Liang"},{"key":"ref27","first-page":"7167","article-title":"A simple unified framework for detecting out-of-distribution samples and adversarial attacks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Lee"},{"key":"ref28","article-title":"Learning confidence for out-of-distribution detection in neural networks","author":"DeVries","year":"2018"},{"key":"ref29","article-title":"Deep anomaly detection with outlier exposure","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Hendrycks"},{"key":"ref30","article-title":"Unsupervised detection of lesions in brain MRI using constrained adversarial auto-encoders","volume-title":"Proc. Med. Imag. Deep Learn.","author":"Chen"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00028"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101839"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101840"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00822"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01321"},{"key":"ref36","article-title":"Auto-encoding variational Bayes","author":"Kingma","year":"2013"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20893-6_39"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.01.010"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00283"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI48211.2021.9434115"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107706"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2018.00201"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.isci.2023.107086"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.86"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/AVSS.2019.8909850"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01333"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01951"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00424"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01466"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3162123"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00717"},{"key":"ref52","article-title":"Early detection and localization of pancreatic cancer by label-free tumor synthesis","volume-title":"Proc. MICCAI Workshop Big Task Small Data","author":"Li"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01934"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-43895-0_4"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-23626-6_2"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2020.12.015"},{"key":"ref57","article-title":"Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the brats challenge","author":"Bakas","year":"2018"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2959609"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2935553"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87589-3_71"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1145\/3464423"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-658-36295-9_5"},{"key":"ref63","first-page":"286","article-title":"The OOD blind spot of unsupervised anomaly detection","volume-title":"Proc. 4th Conf. Med. Imag. Deep Learn.","author":"Heer"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00358"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59050-9_12"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87196-3_18"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-020-03936-1"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3093883"},{"key":"ref69","first-page":"1378","article-title":"Ask me anything: Dynamic memory networks for natural language processing","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kumar"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00210"},{"key":"ref71","article-title":"Learning to remember rare events","author":"Kaiser","year":"2017"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00429"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00153"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00179"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01438"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01517"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102846"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2024.103088"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1145\/3626235"},{"key":"ref80","article-title":"Boosting dermatoscopic lesion segmentation via diffusion models with visual and textual prompts","author":"Du","year":"2023"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16452-1_4"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2023.3290149"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02288"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.21236\/ADA164453"},{"key":"ref85","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW54120.2021.00293"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01163"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3101403"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00304"},{"key":"ref91","article-title":"Neural turing machines","author":"Graves","year":"2014"},{"key":"ref92","article-title":"Categorical reparameterization with Gumbel-Softmax","author":"Jang","year":"2016"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01252-6_6"},{"key":"ref95","article-title":"Attention is all you need","author":"Vaswani","year":"2017"},{"key":"ref96","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"Radford","year":"2015"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00954"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-68799-1_35"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i1.19915"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21735-7_7"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2018.00088"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00301"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI45749.2020.9098406"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87240-3_13"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr52688.2022.01392"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-45676-3_2"},{"key":"ref107","article-title":"A2B-GAN: Utilizing unannotated anomalous images for anomaly detection in medical image analysis","author":"Rahman Siddiquee","year":"2021"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2023.102930"},{"key":"ref109","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301590"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-76550-z"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i1.19915"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.369"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.381"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00144"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00919-9_29"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00778"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102475"}],"container-title":["IEEE Transactions on Pattern Analysis and Machine Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/34\/10627928\/10480307.pdf?arnumber=10480307","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,4]],"date-time":"2025-04-04T19:38:23Z","timestamp":1743795503000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10480307\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9]]},"references-count":119,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tpami.2024.3382009","relation":{},"ISSN":["0162-8828","2160-9292","1939-3539"],"issn-type":[{"value":"0162-8828","type":"print"},{"value":"2160-9292","type":"electronic"},{"value":"1939-3539","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9]]}}}