乐胖代购免代理版

{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,3]],"date-time":"2024-07-03T23:17:57Z","timestamp":1720048677695},"reference-count":30,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T00:00:00Z","timestamp":1630454400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002613","name":"Ulsan National Institute of Science and Technology","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002613","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Pattern Recognition"],"published-print":{"date-parts":[[2021,9]]},"DOI":"10.1016\/j.patcog.2021.107990","type":"journal-article","created":{"date-parts":[[2021,4,20]],"date-time":"2021-04-20T14:09:54Z","timestamp":1618927794000},"page":"107990","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":5,"special_numbering":"C","title":["Two-stage adaptive random Fourier sampling method for image reconstruction"],"prefix":"10.1016","volume":"117","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-4306-0009","authenticated-orcid":false,"given":"Joo Dong","family":"Yun","sequence":"first","affiliation":[]},{"given":"Yunho","family":"Kim","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.patcog.2021.107990_bib0001","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1109\/TIT.2005.862083","article-title":"Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information","volume":"52","author":"Cand\u00e8s","year":"2006","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"3","key":"10.1016\/j.patcog.2021.107990_bib0002","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1088\/0266-5611\/23\/3\/008","article-title":"Sparsity and incoherence in compressive sampling","volume":"23","author":"Cand\u00e8s","year":"2007","journal-title":"Inverse Proble."},{"issue":"3","key":"10.1016\/j.patcog.2021.107990_bib0003","doi-asserted-by":"crossref","first-page":"7235","DOI":"10.1109\/TIT.2011.2161794","article-title":"A probabilistic and PIPless theory of compressed sensing","volume":"57","author":"Cand\u00e8s","year":"2011","journal-title":"IEEE Trans. Inf. Theory"},{"issue":"5","key":"10.1016\/j.patcog.2021.107990_bib0004","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1007\/s10208-015-9276-6","article-title":"Generalized sampling and infinite-dimensional compressed sensing","volume":"16","author":"Adcock","year":"2016","journal-title":"Found. Computat. Math."},{"issue":"5","key":"10.1016\/j.patcog.2021.107990_bib0005","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1109\/LSP.2016.2550101","article-title":"A note on compressed sensing of structured sparse wavelet coefficients from subsampled Fourier measurements","volume":"23","author":"Adcock","year":"2016","journal-title":"IEEE Signal Process. Lett."},{"key":"10.1016\/j.patcog.2021.107990_bib0006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1017\/fms.2016.32","article-title":"Breaking the coherence barrier: a new theory for compressed sensing","volume":"5","author":"Adcock","year":"2017","journal-title":"Forum Math. Sigma"},{"key":"10.1016\/j.patcog.2021.107990_bib0007","article-title":"Utilizing the wavelet transform\u2019s structure in compressed sensing","author":"Dwork","year":"2020","journal-title":"arXiv: Image Video Process."},{"issue":"12","key":"10.1016\/j.patcog.2021.107990_bib0008","doi-asserted-by":"crossref","first-page":"3356","DOI":"10.1109\/78.806079","article-title":"Reconstruction of a compactly supported function from the discrete sampling of its fourier transform","volume":"47","author":"Yin","year":"1999","journal-title":"IEEE Trans. Signal Process."},{"key":"10.1016\/j.patcog.2021.107990_bib0009","doi-asserted-by":"crossref","first-page":"1-16","DOI":"10.1109\/TSP.2019.2952044","article-title":"Tensor completion from regular sub-nyquist samples","volume":"68","author":"Kanatsoulis","year":"2020","journal-title":"Trans. Sig. Proc."},{"issue":"1","key":"10.1016\/j.patcog.2021.107990_bib0010","doi-asserted-by":"crossref","first-page":"487","DOI":"10.1007\/s10915-010-9364-3","article-title":"On reconstruction from non-uniform spectral data","volume":"45","author":"Viswanathan","year":"2010","journal-title":"J. Sci. Comput."},{"issue":"4","key":"10.1016\/j.patcog.2021.107990_bib0011","doi-asserted-by":"crossref","first-page":"1083","DOI":"10.1007\/s10044-017-0666-z","article-title":"A method for liver segmentation in perfusion MR images using probabilistic atlases and viscous reconstruction","volume":"21","author":"Dura","year":"2018","journal-title":"Pattern Anal. Appl."},{"issue":"4","key":"10.1016\/j.patcog.2021.107990_bib0012","doi-asserted-by":"crossref","first-page":"e2811","DOI":"10.1002\/cnm.2811","article-title":"Vessel segmentation from abdominal magnetic resonance images: adaptive and reconstructive approach","volume":"33","author":"Goceri","year":"2017","journal-title":"Int. J. Numer. MethodsBiomed. Eng."},{"issue":"2","key":"10.1016\/j.patcog.2021.107990_bib0013","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/0021-9991(92)90399-J","article-title":"A fast algorithm for chebyshev, Fourier, and Sinc interpolation onto an irregular grid","volume":"103","author":"Boyd","year":"1992","journal-title":"J. Comput. Phys."},{"issue":"6","key":"10.1016\/j.patcog.2021.107990_bib0014","doi-asserted-by":"crossref","first-page":"1368","DOI":"10.1137\/0914081","article-title":"Fast fourier transforms for nonequispaced data","volume":"14","author":"Dutt","year":"1993","journal-title":"SIAM J. Sci. Comput."},{"issue":"3","key":"10.1016\/j.patcog.2021.107990_bib0015","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1137\/S003614450343200X","article-title":"Accelerating the nonuniform fast fourier transform","volume":"46","author":"Greengard","year":"2004","journal-title":"SIAM Rev."},{"issue":"6","key":"10.1016\/j.patcog.2021.107990_bib0016","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1002\/mrm.21391","article-title":"Sparse MRI : the application of compressed sensing for rapid MR imaging","volume":"1195","author":"Lustig","year":"2007","journal-title":"Magn. Reson. Med."},{"issue":"10","key":"10.1016\/j.patcog.2021.107990_bib0017","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1109\/LSP.2011.2163712","article-title":"On variable density compressive sampling","volume":"18","author":"Puy","year":"2011","journal-title":"Signal Process. Lett. IEEE"},{"key":"10.1016\/j.patcog.2021.107990_bib0018","first-page":"1","article-title":"Compressive sensing and structured random matrices","author":"Rauhut","year":"2011","journal-title":"Radon Ser. Comp. Appl. Math."},{"key":"10.1016\/j.patcog.2021.107990_bib0019","series-title":"Optimal variable-density k-space sampling in MRI","first-page":"237","author":"Lee","year":"2004"},{"issue":"2","key":"10.1016\/j.patcog.2021.107990_bib0020","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1109\/TMI.2017.2766131","article-title":"On-the-fly adaptive k-space sampling for linearMRI reconstruction using moment-based spectral analysis","volume":"37","author":"Levine","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"2","key":"10.1016\/j.patcog.2021.107990_bib0021","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1016\/j.acha.2012.08.010","article-title":"How well can we estimate a sparse vector?","volume":"34","author":"Cand\u00e8s","year":"2013","journal-title":"Appl. Comput. Harmonic Anal."},{"issue":"20","key":"10.1016\/j.patcog.2021.107990_bib0022","doi-asserted-by":"crossref","first-page":"5437","DOI":"10.1109\/TSP.2016.2597130","article-title":"Constrained adaptive sensing","volume":"64","author":"Davenport","year":"2016","journal-title":"IEEE Trans. Signal Process."},{"key":"10.1016\/j.patcog.2021.107990_bib0023","first-page":"546814","article-title":"Energy preserved sampling for compressed sensing MRI","volume":"2014","author":"Crum","year":"2014","journal-title":"Comput. Math. Methods Med."},{"issue":"1","key":"10.1016\/j.patcog.2021.107990_bib0024","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1186\/s42490-019-0006-z","article-title":"Compressed sensing MRI: a review from signal processing perspective","volume":"1","author":"Ye","year":"2019","journal-title":"BMC Biomed. Eng."},{"issue":"2","key":"10.1016\/j.patcog.2021.107990_bib0025","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1109\/TIT.2016.2629078","article-title":"Compressive sampling using annihilating filter-based low-rank interpolation","volume":"63","author":"Ye","year":"2017","journal-title":"IEEE Trans. Inf. Theory"},{"key":"10.1016\/j.patcog.2021.107990_bib0026","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1016\/j.patcog.2016.09.040","article-title":"Multi-dimensional low rank plus sparse decomposition for reconstruction of under-sampled dynamic MRI","volume":"63","author":"Roohi","year":"2017","journal-title":"Pattern Recognit."},{"issue":"1","key":"10.1016\/j.patcog.2021.107990_bib0027","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s10334-010-0234-7","article-title":"Adapted random sampling patterns for accelerated MRI","volume":"24","author":"Knoll","year":"2011","journal-title":"Magn. Reson. Mater. Phys. Biol. Med."},{"issue":"7","key":"10.1016\/j.patcog.2021.107990_bib0028","doi-asserted-by":"crossref","first-page":"899","DOI":"10.1016\/j.mri.2013.12.022","article-title":"Adaptive k-space sampling design for edge-enhanced DCE-MRI using compressed sensing","volume":"32","author":"Raja","year":"2014","journal-title":"Magn. Reson. Imaging"},{"key":"10.1016\/j.patcog.2021.107990_bib0029","series-title":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","first-page":"326","article-title":"Signal recovery in perturbed fourier compressed sensing","author":"Pandotra","year":"2018"},{"issue":"2","key":"10.1016\/j.patcog.2021.107990_bib0030","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1109\/TIP.2013.2288004","article-title":"Stable and robust sampling strategies for compressive imaging","volume":"23","author":"Krahmer","year":"2014","journal-title":"IEEE Trans. Image Process."}],"container-title":["Pattern Recognition"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320321001771?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0031320321001771?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T10:24:56Z","timestamp":1672395896000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0031320321001771"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9]]},"references-count":30,"alternative-id":["S0031320321001771"],"URL":"https:\/\/doi.org\/10.1016\/j.patcog.2021.107990","relation":{},"ISSN":["0031-3203"],"issn-type":[{"value":"0031-3203","type":"print"}],"subject":[],"published":{"date-parts":[[2021,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Two-stage adaptive random Fourier sampling method for image reconstruction","name":"articletitle","label":"Article Title"},{"value":"Pattern Recognition","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.patcog.2021.107990","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2021 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"107990"}}