{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:10:50Z","timestamp":1783437050139,"version":"3.54.6"},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T00:00:00Z","timestamp":1648425600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T00:00:00Z","timestamp":1648425600000},"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":[[2022,3,28]]},"DOI":"10.1109\/isbi52829.2022.9761587","type":"proceedings-article","created":{"date-parts":[[2022,4,26]],"date-time":"2022-04-26T19:39:34Z","timestamp":1651001974000},"page":"1-4","source":"Crossref","is-referenced-by-count":2,"title":["LONDN-MRI: Adaptive Local Neighborhood-Based Networks for MR Image Reconstruction from Undersampled Data"],"prefix":"10.1109","author":[{"given":"Shijun","family":"Liang","sequence":"first","affiliation":[{"name":"Michigan State University,Department of Biomedical Engineering,East Lansing,MI,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ashwin","family":"Sreevatsa","sequence":"additional","affiliation":[{"name":"University of Michigan,Department of Electrical &#x0026; Computer Engineering,Ann Arbor,MI,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anish","family":"Lahiri","sequence":"additional","affiliation":[{"name":"University of Michigan,Department of Electrical &#x0026; Computer Engineering,Ann Arbor,MI,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saiprasad","family":"Ravishankar","sequence":"additional","affiliation":[{"name":"Michigan State University,Department of Biomedical Engineering,East Lansing,MI,USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref10","article-title":"Bilevel learning of l1-regularizers with closed-form gradients (BLORC)","author":"ghosh","year":"2022","journal-title":"IEEE ICASSP"},{"key":"ref11","doi-asserted-by":"crossref","first-page":"234","DOI":"10.1007\/978-3-319-24574-4_28","article-title":"U-net: Convolutional networks for biomedical image segmentation","author":"ronneberger","year":"2015","journal-title":"Medical Image Computing and Computer-Assisted Intervention &#x2013; MICCAI 2015"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2017.2713099"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2865356"},{"key":"ref14","first-page":"3456","article-title":"Combining supervised and semi-blind dictionary (Super-BReD) learning for MRI reconstruction","author":"lahiri","year":"2020","journal-title":"Proc Intl Soc Mag Res Med"},{"key":"ref15","first-page":"5546","article-title":"Plug-and-play methods provably converge with properly trained denoisers","volume":"97","author":"ryu","year":"2019","journal-title":"Proceedings of the 36th International Conference on Machine Learning"},{"key":"ref16","article-title":"fastMRI: An Open Dataset and Benchmarks for Accelerated MRI","author":"zbontar","year":"2019"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1148\/ryai.2020190007"},{"key":"ref18","article-title":"mrirecon\/bart: version 0.4.03","author":"uecker","year":"2018"},{"key":"ref19","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/97.803428"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2006.871582"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2010.2090538"},{"key":"ref5","first-page":"1","article-title":"An efficient algorithm for compressed MR imaging using total variation and wavelets","author":"ma","year":"2008","journal-title":"2008 IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2012.2226449"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2013.2255133"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2010.936726"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/42.993128"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2936204"}],"event":{"name":"2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)","location":"Kolkata, India","start":{"date-parts":[[2022,3,28]]},"end":{"date-parts":[[2022,3,31]]}},"container-title":["2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9761376\/9761399\/09761587.pdf?arnumber=9761587","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T21:06:14Z","timestamp":1656363974000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9761587\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,28]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/isbi52829.2022.9761587","relation":{},"subject":[],"published":{"date-parts":[[2022,3,28]]}}}