{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,13]],"date-time":"2026-06-13T20:40:41Z","timestamp":1781383241667,"version":"3.54.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,11,1]],"date-time":"2021-11-01T00:00:00Z","timestamp":1635724800000},"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":["2020AAA0105702"],"award-info":[{"award-number":["2020AAA0105702"]}],"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":["62076230"],"award-info":[{"award-number":["62076230"]}],"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":["U19B2038"],"award-info":[{"award-number":["U19B2038"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University Synergy Innovation Program of Anhui Province","award":["GXXT-2019-025"],"award-info":[{"award-number":["GXXT-2019-025"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2021,11]]},"DOI":"10.1109\/tmi.2021.3080695","type":"journal-article","created":{"date-parts":[[2021,5,17]],"date-time":"2021-05-17T21:49:51Z","timestamp":1621288191000},"page":"3205-3216","source":"Crossref","is-referenced-by-count":15,"title":["Weakly Supervised Neuron Reconstruction From Optical Microscopy Images With Morphological Priors"],"prefix":"10.1109","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0478-7018","authenticated-orcid":false,"given":"Xuejin","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5302-280X","authenticated-orcid":false,"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5191-9637","authenticated-orcid":false,"given":"Jie","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9787-7460","authenticated-orcid":false,"given":"Zhiwei","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2510-8993","authenticated-orcid":false,"given":"Zheng-Jun","family":"Zha","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00660"},{"key":"ref38","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3021493"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.3389\/fnana.2020.00038"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2926568"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1186\/s40708-018-0081-2"},{"key":"ref37","first-page":"4331","article-title":"Learning to reweight examples for robust deep learning","volume":"80","author":"ren","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2858821"},{"key":"ref35","first-page":"2399","article-title":"Manifold regularization: A geometric framework for learning from labeled and unlabeled examples","volume":"7","author":"belkin","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.3389\/fbioe.2019.00202"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2855736"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2623357"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101590"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr237"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2262011600"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-011-9105-2"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2833420"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-016-9302-0"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2515068"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s40708-015-0018-y"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-017-9325-1"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw751"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2013.10.036"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-018-9392-y"},{"key":"ref52","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":"ref10","first-page":"5907","article-title":"SELFIE: Refurbishing unclean samples for robust deep learning","volume":"97","author":"song","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref11","first-page":"8778","article-title":"Generalized cross entropy loss for training deep neural networks with noisy labels","author":"zhang","year":"2018","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413684"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00041"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2020.3009148"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuron.2015.06.036"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2895318"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btq212"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-011-9110-5"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-14-294"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu469"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-015-9278-1"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btt170"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.167"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3662"},{"key":"ref8","first-page":"2309","article-title":"MentorNet: Learning data-driven curriculum for very deep neural networks on corrupted labels","volume":"80","author":"jiang","year":"2018","journal-title":"Proc Int Conf Med Learn (ICML)"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2679713"},{"key":"ref49","article-title":"Multi-class generative adversarial networks with the L2 loss function","volume":"abs 1611 4076","author":"mao","year":"2016","journal-title":"CoRR"},{"key":"ref9","first-page":"960","article-title":"Decoupling ‘when to update’ from ‘how to update","author":"malach","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst (NeurIPS)"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_47"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/s12021-018-9377-x"},{"key":"ref48","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1007\/978-3-319-46723-8_49","article-title":"3D U-Net: Learning dense volumetric segmentation from sparse annotation","volume":"9901","author":"\u00e7i\u00e7ek","year":"2016","journal-title":"Medical Image Computing and Computer-Assisted Intervention—MICCAI 2016"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103884"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00789"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1145\/3343031.3350854"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-67558-9_7"},{"key":"ref43","article-title":"Semantic segmentation using adversarial networks","author":"luc","year":"2016","journal-title":"Proc NIPS Workshop Adversarial Training"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/9590090\/09432857.pdf?arnumber=9432857","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:49:16Z","timestamp":1652194156000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9432857\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11]]},"references-count":52,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2021.3080695","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11]]}}}