{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:20:43Z","timestamp":1792786843336,"version":"4.5.0"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,10,1]],"date-time":"2021-10-01T00:00:00Z","timestamp":1633046400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"General Program (Key Program, Major Research Plan) of National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61876032"],"award-info":[{"award-number":["61876032"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Key-Area Research and Development Program of Guangdong Province, China","award":["2018B010111001"],"award-info":[{"award-number":["2018B010111001"]}]},{"name":"National Key R&D Program of China","award":["2018YFC2000702"],"award-info":[{"award-number":["2018YFC2000702"]}]},{"name":"Scientific and Technical Innovation 2030-\u201cNew Generation Artificial Intelligence\u201d","award":["2020AAA0104100"],"award-info":[{"award-number":["2020AAA0104100"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2021,10]]},"DOI":"10.1109\/tmi.2020.3045775","type":"journal-article","created":{"date-parts":[[2020,12,18]],"date-time":"2020-12-18T16:19:55Z","timestamp":1608308395000},"page":"2656-2671","source":"Crossref","is-referenced-by-count":48,"title":["A Unified Framework for Generalized Low-Shot Medical Image Segmentation With Scarce Data"],"prefix":"10.1109","volume":"40","author":[{"given":"Hengji","family":"Cui","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5969-6987","authenticated-orcid":false,"given":"Dong","family":"Wei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2805-3692","authenticated-orcid":false,"given":"Kai","family":"Ma","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shi","family":"Gu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2195-2847","authenticated-orcid":false,"given":"Yefeng","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2806309"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2010.2046908"},{"key":"ref33","article-title":"Few-shot 3D multi-modal medical image segmentation using generative adversarial learning","author":"kumar mondal","year":"2018","journal-title":"arXiv 1810 12241"},{"key":"ref32","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref31","article-title":"Conditional generative adversarial nets","author":"mirza","year":"2014","journal-title":"arXiv 1411 1784"},{"key":"ref30","first-page":"207","article-title":"Distance metric learning for large margin nearest neighbor classification","volume":"10","author":"weinberger","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref37","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.5244\/C.31.167"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101587"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2897538"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1117\/12.2549060"},{"key":"ref40","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00874"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20351-1_3"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00918"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101693"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2010.09.025"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00534"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01418-6_38"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.89"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.3390\/sym11091066"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1561\/2200000019"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2018.00215"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICEIEC49280.2020.9152261"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00610"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2006.79"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00929"},{"key":"ref7","first-page":"3630","article-title":"Matching networks for one shot learning","author":"vinyals","year":"2016","journal-title":"Proc NeurIPS"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2008.2011119"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00536"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mri.2009.05.040"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2020.101657"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2019.2892409"},{"key":"ref45","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"van der maaten","year":"2008","journal-title":"J Mach Learn Res"},{"key":"ref22","author":"landman","year":"0","journal-title":"2015 MICCAI Multi-Atlas Labeling Beyond the Cranial Vault Workshop and Challenge"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01424-7_27"},{"key":"ref21","article-title":"Rethinking atrous convolution for semantic image segmentation","author":"chen","year":"2017","journal-title":"arXiv 1706 05587"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3389\/fgene.2018.00587"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46976-8_12"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2016.2574816"},{"key":"ref44","first-page":"357","article-title":"Difficulty-aware meta-learning for rare disease diagnosis","author":"li","year":"2020","journal-title":"Proc Int Conf MICCAI"},{"key":"ref26","first-page":"394","article-title":"3D patchwise U-net with transition layers for MR brain segmentation","author":"luna","year":"2018","journal-title":"Proc MICCAI Brain-Lesion Workshop"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.3389\/fpubh.2018.00247"},{"key":"ref25","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf MICCAI"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/9552972\/09298830.pdf?arnumber=9298830","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T10:49:19Z","timestamp":1652179759000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9298830\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,10]]},"references-count":47,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2020.3045775","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,10]]}}}