{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,2]],"date-time":"2026-03-02T23:56:31Z","timestamp":1772495791261,"version":"3.50.1"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100002367","name":"Chinese Academy of Sciences","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002367","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1109\/tmi.2019.2944488","type":"journal-article","created":{"date-parts":[[2019,10,1]],"date-time":"2019-10-01T03:29:26Z","timestamp":1569900566000},"page":"1149-1159","source":"Crossref","is-referenced-by-count":72,"title":["Noise Adaptation Generative Adversarial Network for Medical Image Analysis"],"prefix":"10.1109","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5833-7840","authenticated-orcid":false,"given":"Tianyang","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1786-6188","authenticated-orcid":false,"given":"Jun","family":"Cheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9702-5524","authenticated-orcid":false,"given":"Huazhu","family":"Fu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8764-0622","authenticated-orcid":false,"given":"Zaiwang","family":"Gu","sequence":"additional","affiliation":[]},{"given":"Yuting","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Kang","family":"Zhou","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1626-2040","authenticated-orcid":false,"given":"Shenghua","family":"Gao","sequence":"additional","affiliation":[]},{"given":"Rui","family":"Zheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6281-6505","authenticated-orcid":false,"given":"Jiang","family":"Liu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"1349","article-title":"Texture networks: Feed-forward synthesis of textures and stylized images","author":"ulyanov","year":"2016","journal-title":"Proc ICML"},{"key":"ref38","first-page":"694","article-title":"Perceptual losses for real-time style transfer and super-resolution","volume":"9906","author":"johnson","year":"2016","journal-title":"Vision Computer"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref32","first-page":"1","article-title":"Adversarial feature learning","author":"donahue","year":"2016","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00917"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.278"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.265"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2003.1238384"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.310"},{"key":"ref34","first-page":"1857","article-title":"Learning to discover cross-domain relations with generative adversarial networks","volume":"70","author":"kim","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref28","article-title":"Learning image-to-image translation using paired and unpaired training samples","author":"tripathy","year":"2018","journal-title":"arXiv 1805 03189"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.153"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.723"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-bioeng-071516-044442"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.07.005"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/WACVW.2018.00006"},{"key":"ref21","first-page":"1","article-title":"Semantic segmentation using adversarial networks","author":"luc","year":"2016","journal-title":"Proc NIPS Workshop on Adversarial Training"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2018.07.001"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref26","first-page":"1060","article-title":"Generative adversarial text to image synthesis","author":"reed","year":"2016","journal-title":"Proc 33rd Int Conf Mach Learn"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-018-1072-9"},{"key":"ref10","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume":"1","author":"krizhevsky","year":"2012","journal-title":"Proc 25th Adv Neural Inf Process Syst"},{"key":"ref11","first-page":"234","article-title":"U-Net: Convolutional networks for biomedical image segmentation","volume":"9351","author":"ronneberger","year":"2015","journal-title":"Med Image Comput Comput Assist Interv"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.296"},{"key":"ref12","first-page":"647","article-title":"DeCAF: A deep convolutional activation feature for generic visual recognition","author":"donahue","year":"2014","journal-title":"Proc 31st Int Conf Mach Learn"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.114"},{"key":"ref14","first-page":"2208","article-title":"Deep transfer learning with joint adaptation networks","volume":"70","author":"long","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref15","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref16","first-page":"1486","article-title":"Deep generative image models using a Laplacian pyramid of adversarial networks","author":"denton","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","first-page":"2642","article-title":"Conditional image synthesis with auxiliary classifier GANs","volume":"70","author":"odena","year":"2017","journal-title":"Proc 34th Int Conf Mach Learn"},{"key":"ref18","first-page":"2172","article-title":"InfoGAN: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref19","article-title":"Conditional generative adversarial nets","author":"mirza","year":"2014","journal-title":"arXiv 1411 1784"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1117\/1.JBO.23.1.016013"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853873"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2903562"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2851607"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1117\/12.297921"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1117\/1.429925"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.181"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.7763\/IJCTE.2009.V1.2"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2556080"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.11-7640"},{"key":"ref48","first-page":"99","article-title":"On a measure of divergence between two statistical populations defined by their probability distributions","volume":"35","author":"bhattacharyya","year":"1943","journal-title":"Bull Calcutta Math Soc"},{"key":"ref47","author":"gonzalez","year":"2006","journal-title":"Digital Image Processing"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.265"},{"key":"ref44","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.437"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/9055242\/08852672.pdf?arnumber=8852672","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T13:59:15Z","timestamp":1651067955000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8852672\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":49,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2019.2944488","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,4]]}}}