{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,4]],"date-time":"2026-06-04T04:12:24Z","timestamp":1780546344024,"version":"3.54.1"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61901098"],"award-info":[{"award-number":["61901098"]}],"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":["61973063"],"award-info":[{"award-number":["61973063"]}],"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":["61971118"],"award-info":[{"award-number":["61971118"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["N2026001"],"award-info":[{"award-number":["N2026001"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.3006512","type":"journal-article","created":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T20:27:41Z","timestamp":1593721661000},"page":"133470-133487","source":"Crossref","is-referenced-by-count":39,"title":["Single Low-Dose CT Image Denoising Using a Generative Adversarial Network With Modified U-Net Generator and Multi-Level Discriminator"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9748-5619","authenticated-orcid":false,"given":"Jianning","family":"Chi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9906-5493","authenticated-orcid":false,"given":"Chengdong","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaosheng","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Ji","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1628-1404","authenticated-orcid":false,"given":"Hao","family":"Chu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Conditional generative adversarial nets","author":"mirza","year":"2014","journal-title":"arXiv 1411 1784"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2708987"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2917258"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.01.015"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2805692"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2018.8513453"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2018.8546286"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00333"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2018.2858147"},{"key":"ref34","first-page":"2672","article-title":"Generative adversarial nets","volume":"2","author":"goodfellow","year":"2014","journal-title":"Proc 27th Int Conf Neural Inf Process Syst"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2715284"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1364\/BOE.8.000679"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12344"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(04)15433-0"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"2277","DOI":"10.1056\/NEJMra072149","article-title":"Computed tomography&#x2014;An increasing source of radiation exposure","volume":"357","author":"brenner","year":"2007","journal-title":"New England J Med"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2600249"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2005.38"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2757035"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1117\/12.2006907"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2007.901238"},{"key":"ref26","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.881199"},{"key":"ref50","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Medical Image Computing and Computer Assisted Intervention (MICCAI)"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref57","year":"2020","journal-title":"Low Dose CT Grand Challenge"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-013-9622-7"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.12.057"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref52","article-title":"Inception-v4, inception-ResNet and the impact of residual connections on learning","author":"szegedy","year":"2016","journal-title":"arXiv 1602 07261"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2643009"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1118\/1.3638125"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66179-7_48"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/58\/16\/5803"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/55\/18\/009"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2706065"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TRPMS.2018.2810221"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2012.2187213"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2015132766"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2011.2175233"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2766185"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2006.882141"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1117\/12.595662"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2739841"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1118\/1.3232004"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.09.2397"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2012.01.003"},{"key":"ref49","article-title":"Improved training of wasserstein GANs","author":"gulrajani","year":"2017","journal-title":"arXiv 1704 00028"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2765760"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00928-1_18"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2019.2922851"},{"key":"ref47","article-title":"Sharpness-aware low dose CT denoising using conditional generative adversarial network","author":"yi","year":"2017","journal-title":"arXiv 1708 06453"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2827462"},{"key":"ref41","first-page":"694","article-title":"Perceptual losses for real-time style transfer and super-resolution","author":"johnson","year":"2016","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2832217"},{"key":"ref43","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09131783.pdf?arnumber=9131783","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T15:57:38Z","timestamp":1642003058000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9131783\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":57,"URL":"https:\/\/doi.org\/10.1109\/access.2020.3006512","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]}}}