{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T12:44:09Z","timestamp":1774615449598,"version":"3.50.1"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"12","license":[{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2017,12,1]],"date-time":"2017-12-01T00:00:00Z","timestamp":1512086400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01EB013293"],"award-info":[{"award-number":["R01EB013293"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01AG052653"],"award-info":[{"award-number":["R01AG052653"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Med. Imaging"],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1109\/tmi.2017.2753138","type":"journal-article","created":{"date-parts":[[2017,9,15]],"date-time":"2017-09-15T18:44:04Z","timestamp":1505501044000},"page":"2479-2486","source":"Crossref","is-referenced-by-count":218,"title":["Iterative Low-Dose CT Reconstruction With Priors Trained by Artificial Neural Network"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3204-3502","authenticated-orcid":false,"given":"Dufan","family":"Wu","sequence":"first","affiliation":[{"name":"Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9860-072X","authenticated-orcid":false,"given":"Kyungsang","family":"Kim","sequence":"additional","affiliation":[{"name":"Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA"}]},{"given":"Georges","family":"El Fakhri","sequence":"additional","affiliation":[{"name":"Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA"}]},{"given":"Quanzheng","family":"Li","sequence":"additional","affiliation":[{"name":"Gordon Center for Medical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1973.4309314"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/44\/2\/019"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2006.881199"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/42.870265"},{"key":"ref31","author":"abadi","year":"2016","journal-title":"Tensorflow Large-scale machine learning on heterogeneous distributed systems"},{"key":"ref30","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2011.2175233"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref35","year":"2017","journal-title":"SPAMS"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2007.909108"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390294"},{"key":"ref40","doi-asserted-by":"crossref","first-page":"3e","DOI":"10.5334\/jors.ac","article-title":"Mahotas: Open source software for scriptable computer vision","volume":"1","author":"coelho","year":"2013","journal-title":"Journal of Open Research Software"},{"key":"ref11","first-page":"1","author":"ng","year":"2011","journal-title":"Sparse Autoencoder"},{"key":"ref12","first-page":"52","article-title":"Stacked convolutional auto-encoders for hierarchical feature extraction","volume":"6791","author":"masci","year":"2011","journal-title":"Artificial Neural Networks in Machine Learning"},{"key":"ref13","first-page":"2791","article-title":"Winner-take-all autoencoders","author":"makhzani","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref14","author":"larsen","year":"2015","journal-title":"Autoencoding beyond pixels using a learned similarity metric"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6247952"},{"key":"ref16","first-page":"341","article-title":"Image denoising and inpainting with deep neural networks","author":"xie","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref17","author":"kang","year":"2016","journal-title":"A deep convolutional neural network using directionalwavelets for low-dose X-ray CT reconstruction"},{"key":"ref18","author":"ledig","year":"2016","journal-title":"Photo-realistic single image super-resolution using a generative adversarial network"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2713099"},{"key":"ref28","first-page":"797","article-title":"Escaping from saddle points—Online stochastic gradient for tensor decomposition","author":"ge","year":"2015","journal-title":"Proc Conf Learn Theory"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.2214\/AJR.12.9382"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1097\/RLI.ob013e3181dzfeec"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2380993"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-013-0677-5"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/53\/17\/021"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/58\/12\/4047"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"1682","DOI":"10.1109\/TMI.2012.2195669","article-title":"Low-dose X-ray CT reconstruction via dictionary learning","volume":"31","author":"xu","year":"2012","journal-title":"IEEE Trans Med Imag"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/42.802758"},{"key":"ref9","author":"kingma","year":"2013","journal-title":"Auto-encoding variational bayes"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2303021726"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI.2016.7493320"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1364\/BOE.8.000679"},{"key":"ref21","author":"chen","year":"2017","journal-title":"Low-dose CT with a residual encoderdecoder convolutional neural network (RED-CNN)"},{"key":"ref24","year":"2016","journal-title":"Low Dose CT Grand Challenge"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2498148"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2708987"},{"key":"ref26","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref25","author":"goodfellow","year":"2016","journal-title":"Deep Learning"}],"container-title":["IEEE Transactions on Medical Imaging"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/42\/8124116\/08038851.pdf?arnumber=8038851","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,18]],"date-time":"2024-03-18T18:59:29Z","timestamp":1710788369000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8038851\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12]]},"references-count":41,"journal-issue":{"issue":"12"},"URL":"https:\/\/doi.org\/10.1109\/tmi.2017.2753138","relation":{},"ISSN":["0278-0062","1558-254X"],"issn-type":[{"value":"0278-0062","type":"print"},{"value":"1558-254X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,12]]}}}