{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T16:26:33Z","timestamp":1778257593970,"version":"3.51.4"},"reference-count":76,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,1]],"date-time":"2023-05-01T00:00:00Z","timestamp":1682899200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62176249"],"award-info":[{"award-number":["62176249"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["32071459"],"award-info":[{"award-number":["32071459"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61972217"],"award-info":[{"award-number":["61972217"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62006133"],"award-info":[{"award-number":["62006133"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62271465"],"award-info":[{"award-number":["62271465"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62081360152"],"award-info":[{"award-number":["62081360152"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province in China","doi-asserted-by":"publisher","award":["2019B1515120049"],"award-info":[{"award-number":["2019B1515120049"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003453","name":"Natural Science Foundation of Guangdong Province in China","doi-asserted-by":"publisher","award":["2020B1111340056"],"award-info":[{"award-number":["2020B1111340056"]}],"id":[{"id":"10.13039\/501100003453","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2023,5]]},"DOI":"10.1109\/tmi.2022.3232572","type":"journal-article","created":{"date-parts":[[2022,12,29]],"date-time":"2022-12-29T18:40:08Z","timestamp":1672339208000},"page":"1546-1562","source":"Crossref","is-referenced-by-count":20,"title":["Semi-Supervised CT Lesion Segmentation Using Uncertainty-Based Data Pairing and SwapMix"],"prefix":"10.1109","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9292-2744","authenticated-orcid":false,"given":"Pengchong","family":"Qiao","sequence":"first","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8029-1498","authenticated-orcid":false,"given":"Han","family":"Li","sequence":"additional","affiliation":[{"name":"Center for Medical Imaging, Robotics, Analytic Computing and Learning (MIRACLE), School of Biomedical Engineering, Suzhou Institute for Advanced Research, University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5452-3697","authenticated-orcid":false,"given":"Guoli","family":"Song","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6010-1792","authenticated-orcid":false,"given":"Hu","family":"Han","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiqiang","family":"Gao","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2978-5935","authenticated-orcid":false,"given":"Yonghong","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0891-5577","authenticated-orcid":false,"given":"Yongsheng","family":"Liang","sequence":"additional","affiliation":[{"name":"Peng Cheng Laboratory, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xi","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Gastroenterology, Peking University Shenzhen Hospital, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6881-4444","authenticated-orcid":false,"given":"S. Kevin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Center for Medical Imaging, Robotics, Analytic Computing and Learning (MIRACLE), School of Biomedical Engineering, Suzhou Institute for Advanced Research, University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Electronic and Computer Engineering, Peking University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","first-page":"5580","article-title":"What uncertainties do we need in Bayesian deep learning for computer vision?","author":"kendall","year":"2017","journal-title":"Proc NIPS"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3001810"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101766"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3000314"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66185-8_29"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102205"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.89"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3058783"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2995965"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/abc04e"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1148\/ryct.2020200075"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00264"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1148\/ryct.2020200082"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2996645"},{"key":"ref16","first-page":"109","article-title":"Efficient inference in fully connected CRFs with Gaussian edge potentials","volume":"24","author":"kr\u00e4henb\u00fchl","year":"2011","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2022.102530"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2995319"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.2993291"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-020-0931-3"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3066161"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00934-2_81"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101910"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3117564"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-28100-x"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-0694-9_52"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2014.12.008"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2012.12.004"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-18685-1"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01269"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00406"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00683"},{"key":"ref4","first-page":"605","article-title":"Uncertainty-aware self-ensembling model for semi-supervised 3D left atrium segmentation","author":"yu","year":"2019","journal-title":"Proc MICCAI"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2857800"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00126"},{"key":"ref5","first-page":"1","article-title":"Semi-supervised semantic segmentation needs strong, varied perturbations","author":"french","year":"2020","journal-title":"Proc BMVC"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2005.862753"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00057"},{"key":"ref34","article-title":"FMix: Enhancing mixed sample data augmentation","author":"harris","year":"2020","journal-title":"arXiv 2002 12047"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20351-1_3"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_39"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2021.3117888"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176348768"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3006437"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref32","first-page":"1","article-title":"Mixup: Beyond empirical risk minimization","author":"zhang","year":"2018","journal-title":"Proc ICLR"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.107"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1038\/s41592-020-01008-z"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.06.014"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00401"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00348"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2017.04.006"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-69817-y"},{"key":"ref73","first-page":"1","article-title":"Wilcoxon signed-rank test","author":"woolson","year":"2007","journal-title":"Wiley Encyclopedia of Clinical Trials"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2019.06.003"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i10.17066"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2845918"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59710-8_54"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00889-5_1"},{"key":"ref26","first-page":"1050","article-title":"Dropout as a Bayesian approximation: Representing model uncertainty in deep learning","author":"gal","year":"2016","journal-title":"Proc ICML"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1992.4.3.448"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858821"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-23911-3_16"},{"key":"ref64","first-page":"1","article-title":"A probabilistic U-Net for segmentation of ambiguous images","volume":"31","author":"kohl","year":"2018","journal-title":"Proc NIPS"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9622-7"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-23911-3_18"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-23911-3_1"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2010.08.005"},{"key":"ref28","article-title":"Simple and scalable predictive uncertainty estimation using deep ensembles","author":"lakshminarayanan","year":"2016","journal-title":"arXiv 1612 01474"},{"key":"ref27","first-page":"4907","article-title":"Bayesian uncertainty estimation for batch normalized deep networks","author":"teye","year":"2018","journal-title":"Proc ICML"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3000949"},{"key":"ref60","first-page":"5049","article-title":"Mixmatch: A holistic approach to semi-supervised learning","author":"berthelot","year":"2019","journal-title":"Proc NIPS"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1118\/1.3528204"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01485"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/10114431\/10002838.pdf?arnumber=10002838","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,22]],"date-time":"2023-05-22T17:52:06Z","timestamp":1684777926000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10002838\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5]]},"references-count":76,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2022.3232572","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,5]]}}}