{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T04:19:55Z","timestamp":1754108395184,"version":"3.28.0"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,11,1]],"date-time":"2020-11-01T00:00:00Z","timestamp":1604188800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,11,1]]},"DOI":"10.1109\/ieeeconf51394.2020.9443547","type":"proceedings-article","created":{"date-parts":[[2021,6,4]],"date-time":"2021-06-04T01:32:35Z","timestamp":1622770355000},"page":"1405-1409","source":"Crossref","is-referenced-by-count":5,"title":["Momentum-Net for Low-Dose CT Image Reconstruction"],"prefix":"10.1109","author":[{"given":"Siqi","family":"Ye","sequence":"first","affiliation":[{"name":"University of Michigan - Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University,Shanghai,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yong","family":"Long","sequence":"additional","affiliation":[{"name":"University of Michigan - Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University,Shanghai,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Il Yong","family":"Chun","sequence":"additional","affiliation":[{"name":"University of Hawai’i at Manoa,Department of Electrical Engineering,HI,USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2017.2715284"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2823756"},{"article-title":"Sparse-view X-ray CT reconstruction using ? 1 prior with learned transform","year":"2019","author":"zheng","key":"ref12"},{"article-title":"Improved low-count quantitative PET reconstruction with an iterative neural network","year":"2019","author":"lim","key":"ref13"},{"key":"ref14","article-title":"BCD-Net for low-dose CT reconstruction: Acceleration, convergence, and generalization","author":"chun","year":"2019","journal-title":"Proc Med Image Computing and Computer Assist Interven"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/IVMSPW.2018.8448694"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2713099"},{"key":"ref17","first-page":"10","article-title":"Deep ADMM-Net for compressive sensing MRI","volume":"29","author":"yang","year":"2016","journal-title":"Proc NIPS"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TCI.2016.2629286"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2020.3012955"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1088\/0031-9155\/58\/12\/R63"},{"key":"ref27","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Proc ICLR 2015"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/42.993128"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2832007"},{"key":"ref5","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":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2937734"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2761545"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1117\/3.831079.ch1"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2019.2921446"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1364\/JOSAA.1.000612"},{"key":"ref20","first-page":"5546","article-title":"Plug-and-play methods provably converge with properly trained denoisers","author":"ryu","year":"2019","journal-title":"International Conference on Machine Learning (ICML)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/42.293921"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/s10107-012-0629-5"},{"key":"ref24","first-page":"30","article-title":"Efficient compressed sensing statistical X-ray CT reconstruction from fewer measurements","author":"chun","year":"2013","journal-title":"Proc Intl Mtg on Fully 3D Image Recon in Rad and Nuc Med"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2627004"},{"key":"ref26","article-title":"SPULTRA: Low-dose CT image reconstruction with joint statistical and learned image models","author":"ye","year":"2019","journal-title":"IEEE Trans on Med Imag"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1118\/1.4957556"}],"event":{"name":"2020 54th Asilomar Conference on Signals, Systems, and Computers","start":{"date-parts":[[2020,11,1]]},"location":"Pacific Grove, CA, USA","end":{"date-parts":[[2020,11,4]]}},"container-title":["2020 54th Asilomar Conference on Signals, Systems, and Computers"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9443248\/9443268\/09443547.pdf?arnumber=9443547","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,2]],"date-time":"2022-08-02T23:58:14Z","timestamp":1659484694000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9443547\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,1]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/ieeeconf51394.2020.9443547","relation":{},"subject":[],"published":{"date-parts":[[2020,11,1]]}}}