{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T09:25:40Z","timestamp":1781169940145,"version":"3.54.1"},"reference-count":69,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T00:00:00Z","timestamp":1701388800000},"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":["62373278"],"award-info":[{"award-number":["62373278"]}],"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":["21JCJQJC00130"],"award-info":[{"award-number":["21JCJQJC00130"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Taishan Industrial Experts Program"},{"name":"STI 2030-Major Projects","award":["2021ZD0201600"],"award-info":[{"award-number":["2021ZD0201600"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE J. Biomed. Health Inform."],"published-print":{"date-parts":[[2023,12]]},"DOI":"10.1109\/jbhi.2023.3321602","type":"journal-article","created":{"date-parts":[[2023,10,3]],"date-time":"2023-10-03T17:54:26Z","timestamp":1696355666000},"page":"5914-5925","source":"Crossref","is-referenced-by-count":16,"title":["WS-MTST: Weakly Supervised Multi-Label Brain Tumor Segmentation With Transformers"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0890-1826","authenticated-orcid":false,"given":"Huazhen","family":"Chen","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9108-6182","authenticated-orcid":false,"given":"Jianpeng","family":"An","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6758-9940","authenticated-orcid":false,"given":"Bochang","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5731-8026","authenticated-orcid":false,"given":"Lili","family":"Xia","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6339-122X","authenticated-orcid":false,"given":"Yunhao","family":"Bai","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9551-202X","authenticated-orcid":false,"given":"Zhongke","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1093\/jnci\/91.16.1382"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJM200101113440207"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/58\/13\/R97"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.ncl.2007.07.010"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1002\/cpe.4962"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2013.05.002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2022.106405"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.004"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-90428-8"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-04435-9_39"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_20"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32248-9_24"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-32239-7_81"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3002244"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2021.108341"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_65"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2021.102315"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-006-7934-5"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1016\/0021-9991(88)90002-2"},{"key":"ref20","first-page":"12116","article-title":"Do vision transformers see like convolutional neural networks?","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Raghu","year":"2021"},{"key":"ref21","article-title":"An image is worth 16x16 words: Transformers for image recognition at scale","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Dosovitskiy","year":"2021"},{"key":"ref22","first-page":"10347","article-title":"Training data-efficient image transformers & distillation through attention","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Touvron","year":"2021"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"ref24","article-title":"TransUNet: Transformers make strong encoders for medical image segmentation","author":"Chen","year":"2021"},{"key":"ref25","first-page":"12077","article-title":"SegFormer: Simple and efficient design for semantic segmentation with transformers","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Xie","year":"2021"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01196"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2023.3260026"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2023.03.028"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2022.104034"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR56361.2022.9956705"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-87193-2_11"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-16443-9_16"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00951"},{"key":"ref34","article-title":"BEiT: BERT pre-training of image transformers","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Bao","year":"2022"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"ref36","first-page":"21271","article-title":"Bootstrap your own latent - a new approach to self-supervised learning","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Grill","year":"2020"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"ref38","first-page":"1597","article-title":"A simple framework for contrastive learning of visual representations","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Chen","year":"2020"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01634"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01641"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01141"},{"key":"ref43","first-page":"655","article-title":"Causal intervention for weakly-supervised semantic segmentation","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Zhang","year":"2020"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00901"},{"key":"ref45","article-title":"How much position information do convolutional neural networks encode","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Islam","year":"2020"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00061"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00427"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref49","first-page":"201","article-title":"Why does unsupervised pre-training help deep learning","volume":"9","author":"Erhan","year":"2010","journal-title":"J. Mach. Learn. Res."},{"key":"ref50","first-page":"12546","article-title":"Contrastive learning of global and local features for medical image segmentation with limited annotations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Chaitanya","year":"2020"},{"key":"ref51","first-page":"16686","article-title":"Self-paced contrastive learning for semi-supervised medical image segmentation with meta-labels","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Peng","year":"2021"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00431"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00523"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01875"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-59137-3_23"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00231"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00302"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i3.25408"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.01057"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-72084-1_30"},{"key":"ref62","first-page":"109","article-title":"Efficient inference in fully connected CRFs with Gaussian edge potentials","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Krhenbhl","year":"2011"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2835303"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00045"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00943"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref69","first-page":"6105","article-title":"EfficientNet: Rethinking model scaling for convolutional neural networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Tan","year":"2019"}],"container-title":["IEEE Journal of Biomedical and Health Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221020\/10345388\/10269670.pdf?arnumber=10269670","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,20]],"date-time":"2023-12-20T01:25:06Z","timestamp":1703035506000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10269670\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12]]},"references-count":69,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/jbhi.2023.3321602","relation":{},"ISSN":["2168-2194","2168-2208"],"issn-type":[{"value":"2168-2194","type":"print"},{"value":"2168-2208","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12]]}}}