{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T09:06:15Z","timestamp":1772010375335,"version":"3.50.1"},"reference-count":61,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"10","license":[{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,1]],"date-time":"2020-10-01T00:00:00Z","timestamp":1601510400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006775","name":"GE Healthcare","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006775","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005492","name":"Stanford University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005492","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2020,10]]},"DOI":"10.1109\/tmi.2020.2987026","type":"journal-article","created":{"date-parts":[[2020,4,10]],"date-time":"2020-04-10T16:47:46Z","timestamp":1586537266000},"page":"3089-3099","source":"Crossref","is-referenced-by-count":50,"title":["Synthesize High-Quality Multi-Contrast Magnetic Resonance Imaging From Multi-Echo Acquisition Using Multi-Task Deep Generative Model"],"prefix":"10.1109","volume":"39","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1622-5664","authenticated-orcid":false,"given":"Guanhua","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4002-909X","authenticated-orcid":false,"given":"Enhao","family":"Gong","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]},{"given":"Suchandrima","family":"Banerjee","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]},{"given":"Dann","family":"Martin","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, Tsinghua University, Beijing, China"}]},{"given":"Elizabeth","family":"Tong","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0363-0468","authenticated-orcid":false,"given":"Jay","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]},{"given":"Huijun","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA"}]},{"given":"Max","family":"Wintermark","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5918-4172","authenticated-orcid":false,"given":"John M.","family":"Pauly","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5781-8848","authenticated-orcid":false,"given":"Greg","family":"Zaharchuk","sequence":"additional","affiliation":[{"name":"Department of Radiology, Stanford University, Stanford, CA, USA"}]}],"member":"263","reference":[{"key":"ref39","article-title":"Deep generative adversarial networks for compressed sensing automates MRI","author":"mardani","year":"2017","journal-title":"arXiv 1706 00051"},{"key":"ref38","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":"ref33","first-page":"2795","article-title":"Improved synthetic MRI from multi-echo MRI using deep learning","author":"gong","year":"2018","journal-title":"Proceedings of the 26th Annual Meeting"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00928-1_60"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.101552"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2764326"},{"key":"ref37","article-title":"Multimodal unsupervised image-to-image translation","author":"huang","year":"2018","journal-title":"arXiv 1804 04732"},{"key":"ref36","article-title":"Star-GAN: Unified generative adversarial networks for multi-domain image-to-image translation","author":"choi","year":"2017","journal-title":"arXiv 1711 09020"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.632"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363592"},{"key":"ref60","article-title":"MedGAN: Medical image translation using GANs","author":"armanious","year":"2018","journal-title":"arXiv 1806 06397"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2894692"},{"key":"ref28","article-title":"Synergistic reconstruction and synthesis via generative adversarial networks for accelerated multi-contrast MRI","author":"dar","year":"2018","journal-title":"arXiv 1805 10704"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2945521"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2018.2883958"},{"key":"ref2","first-page":"265","article-title":"Cerebral magnetic resonance image synthesis","volume":"6","author":"bobman","year":"1985","journal-title":"Amer J Neuroradiol"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiology.153.1.6089265"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2018.2814538"},{"key":"ref22","first-page":"3130","article-title":"A deep learning approach to synthesize flair image from T1WI and T2WI","author":"abe","year":"2018","journal-title":"Proceedings of the 26th Annual Meeting"},{"key":"ref21","first-page":"3490","article-title":"Mr image synthesis using a deep learning based data-driven approach","author":"liu","year":"2018","journal-title":"Proceedings of the 26th Annual Meeting"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.19"},{"key":"ref23","first-page":"234","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363653"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24553-9_83"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2018.8363523"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1177\/2058460118769686"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.25970"},{"key":"ref58","article-title":"200x low-dose PET reconstruction using deep learning","author":"xu","year":"2017","journal-title":"arXiv 1712 04119"},{"key":"ref57","article-title":"Uncertainty analysis of VAE-GANs for compressive medical imaging","author":"edupuganti","year":"2019","journal-title":"arXiv 1901 11228"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.244"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2820120"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/3020461"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00259"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177703732"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A5227"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6560\/aada6d"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2017.7950457"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1002\/mp.12155"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68127-6_2"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2018180940"},{"key":"ref15","first-page":"455","article-title":"Synthesizing missing PET from MRI with cycle-consistent generative adversarial networks for Alzheimer&#x2019;s disease diagnosis","author":"pan","year":"2018","journal-title":"Proc Int Conf Med Image Comput Comput -Assist Intervent"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.117.198051"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2017170700"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2901750"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2019.2895894"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/nature11971"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21165"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/jmri.26712"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.0000000000000365"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1258\/ar.2012.120195"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1002\/mrm.21635"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2010.2090538"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3174\/ajnr.A4665"},{"key":"ref46","first-page":"8024","article-title":"Pytorch: An imperative style, high-performance deep learning library","author":"paszke","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2016.78"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2010.579"},{"key":"ref47","author":"osborn","year":"2013","journal-title":"Osborn&#x2019;s Brain Imaging Pathology and Anatomy"},{"key":"ref42","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00928-1_27"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.304"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/9210240\/09063444.pdf?arnumber=9063444","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T17:40:53Z","timestamp":1760377253000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9063444\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10]]},"references-count":61,"journal-issue":{"issue":"10"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2020.2987026","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10]]}}}