{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,7]],"date-time":"2024-07-07T23:56:13Z","timestamp":1720396573580},"reference-count":60,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2020,2,1]],"date-time":"2020-02-01T00:00:00Z","timestamp":1580515200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51675437","51605389"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006579","name":"Ministry of Industry and Information Technology of China","doi-asserted-by":"publisher","award":["MJ-2017-F-05"],"id":[{"id":"10.13039\/501100006579","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012429","name":"Central Universities","doi-asserted-by":"publisher","award":["31020190504006"],"id":[{"id":"10.13039\/501100012429","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2019M653749"],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Neurocomputing"],"published-print":{"date-parts":[[2020,2]]},"DOI":"10.1016\/j.neucom.2019.09.087","type":"journal-article","created":{"date-parts":[[2019,10,17]],"date-time":"2019-10-17T23:25:46Z","timestamp":1571354746000},"page":"65-78","update-policy":"http:\/\/dx.doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":10,"special_numbering":"C","title":["Streaking artifacts suppression for cone-beam computed tomography with the residual learning in neural network"],"prefix":"10.1016","volume":"378","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-1724-5293","authenticated-orcid":false,"given":"Fuqiang","family":"Yang","sequence":"first","affiliation":[]},{"given":"Dinghua","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Hua","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Kuidong","family":"Huang","sequence":"additional","affiliation":[]},{"given":"You","family":"Du","sequence":"additional","affiliation":[]},{"given":"Mingxuan","family":"Teng","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"13","key":"10.1016\/j.neucom.2019.09.087_bib0001","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/aaca14","article-title":"Optimization based beam-hardening correction in CT under data integral invariant constraint","volume":"63","author":"Tang","year":"2018","journal-title":"Phys. Med. Biol."},{"issue":"3","key":"10.1016\/j.neucom.2019.09.087_bib0002","doi-asserted-by":"crossref","DOI":"10.1088\/1674-1137\/39\/3\/038202","article-title":"Point spread function modeling and image restoration for cone-beam CT","volume":"39","author":"Zhang","year":"2015","journal-title":"Chin. Phys. C"},{"issue":"5","key":"10.1016\/j.neucom.2019.09.087_bib0003","doi-asserted-by":"crossref","first-page":"3955","DOI":"10.1109\/TNS.2013.2274481","article-title":"Straight-line-trajectory-based X-ray tomographic imaging for security inspections: system design, image reconstruction and preliminary results","volume":"60","author":"Gao","year":"2013","journal-title":"IEEE Trans. Nucl. Sci."},{"issue":"2","key":"10.1016\/j.neucom.2019.09.087_bib0004","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6501\/aa9a07","article-title":"Incomplete projection reconstruction of computed tomography based on modified discrete algebraic reconstruction technique","volume":"29","author":"Yang","year":"2018","journal-title":"Meas. Sci. Technol."},{"issue":"6","key":"10.1016\/j.neucom.2019.09.087_bib0005","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1109\/TBME.2017.2711478","article-title":"Three-Dimensional weighting in cone beam FBP reconstruction and its transformation over geometries","volume":"65","author":"Tang","year":"2018","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"18","key":"10.1016\/j.neucom.2019.09.087_bib0006","doi-asserted-by":"crossref","first-page":"5949","DOI":"10.1088\/0031-9155\/56\/18\/011","article-title":"Low-dose CT reconstruction via edge-preserving total variation regularization","volume":"56","author":"Zhen","year":"2011","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.neucom.2019.09.087_bib0007","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1016\/j.apm.2018.07.006","article-title":"Low-dose spectral CT reconstruction using image gradient \u21130\u2013norm and tensor dictionary","volume":"63","author":"Wu","year":"2018","journal-title":"Appl. Math. Model."},{"issue":"3","key":"10.1016\/j.neucom.2019.09.087_bib0008","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1109\/TMI.2015.2498148","article-title":"Extracting information from previous full-dose CT scan for knowledge-based Bayesian reconstruction of current low-dose CT images","volume":"35","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"2","key":"10.1016\/j.neucom.2019.09.087_bib0009","first-page":"227","article-title":"Image artifacts and noise reduction algorithm for cone-beam computed tomography with low-signal projections","volume":"26","author":"Yang","year":"2018","journal-title":"J. Xray Sci. Technol."},{"issue":"22","key":"10.1016\/j.neucom.2019.09.087_bib0010","first-page":"1","article-title":"Sparse-View image reconstruction in cone-beam computed tomography with variance-reduced stochastic gradient descent and locally-adaptive proximal operation","volume":"37","author":"Karimi","year":"2017","journal-title":"J.Med. Biol. Eng."},{"issue":"6","key":"10.1016\/j.neucom.2019.09.087_bib0011","doi-asserted-by":"crossref","first-page":"1418","DOI":"10.1109\/TMI.2018.2823768","article-title":"Framing U-Net via deep convolutional framelets: application to sparse-view CT","volume":"37","author":"Han","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"5","key":"10.1016\/j.neucom.2019.09.087_bib0012","article-title":"Review of reconstruction algorithms with incomplete projection data of computed tomography","volume":"63","author":"Yang","year":"2014","journal-title":"Acta Phys. Sin."},{"issue":"10","key":"10.1016\/j.neucom.2019.09.087_bib0013","doi-asserted-by":"crossref","first-page":"2221","DOI":"10.1364\/OL.43.002221","article-title":"Sparsity-based reconstruction for super-resolved limited-view photoacoustic computed tomography deep in a scattering medium","volume":"43","author":"Egolf","year":"2018","journal-title":"Opt. Lett."},{"key":"10.1016\/j.neucom.2019.09.087_bib0014","article-title":"A joint reconstruction and segmentation method for limited-angle X-Ray tomography","volume":"6","author":"Wei","year":"2018","journal-title":"IEEE Access"},{"issue":"15","key":"10.1016\/j.neucom.2019.09.087_bib0015","doi-asserted-by":"crossref","DOI":"10.1088\/1361-6560\/aacece","article-title":"Compressed sensing based CT reconstruction algorithm combined with modified Canny edge detection","volume":"63","author":"Hsieh","year":"2018","journal-title":"Phys. Med. Biol."},{"issue":"1","key":"10.1016\/j.neucom.2019.09.087_bib0016","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s40846-017-0288-3","article-title":"A new voxelization strategy in compressed-sensing (CS)-based iterative CT reconstruction for reducing computational cost: simulation and experimental studies","volume":"38","author":"Kim","year":"2018","journal-title":"J. Med. Biol. Eng."},{"issue":"18","key":"10.1016\/j.neucom.2019.09.087_bib0017","doi-asserted-by":"crossref","first-page":"6878","DOI":"10.1088\/0031-9155\/61\/18\/6878","article-title":"Non-local (NLTV) minimization combined with reweighted l1-norm for compressed sensing CT reconstruction","volume":"61","author":"Kim","year":"2016","journal-title":"Phys. Med. Biol."},{"issue":"7","key":"10.1016\/j.neucom.2019.09.087_bib0018","doi-asserted-by":"crossref","first-page":"2039","DOI":"10.1007\/s00330-015-4044-1","article-title":"Prior image constrained compressed sensing metal artifact reduction (piccs-mar): 2D and 3D image quality improvement with hip prostheses at CT colonography","volume":"26","author":"Bannas","year":"2016","journal-title":"Eur. Radiol."},{"issue":"18","key":"10.1016\/j.neucom.2019.09.087_bib0019","doi-asserted-by":"crossref","first-page":"6707","DOI":"10.1088\/0031-9155\/61\/18\/6707","article-title":"Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography","volume":"61","author":"Yu","year":"2016","journal-title":"Phys. Med. Biol."},{"issue":"6","key":"10.1016\/j.neucom.2019.09.087_bib0020","doi-asserted-by":"crossref","first-page":"1511","DOI":"10.1109\/TMI.2018.2829896","article-title":"Statistical iterative CBCT reconstruction based on neural network","volume":"37","author":"Chen","year":"2018","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"6","key":"10.1016\/j.neucom.2019.09.087_bib0021","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1109\/TAC.2015.2471755","article-title":"Robust distributed consensus using total variation","volume":"61","author":"Ben-Ameur","year":"2016","journal-title":"IEEE Trans. Automat. Control"},{"key":"10.1016\/j.neucom.2019.09.087_bib0022","first-page":"25","article-title":"Multiple degree total variation (MDTV) regularization for image restoration","author":"Hu","year":"2016","journal-title":"IEEE Int. Conf. Image Process, IEEE Phoenix AZ USA"},{"issue":"19","key":"10.1016\/j.neucom.2019.09.087_bib0023","article-title":"Image reconstruction algorithm based on inexact alternating direction total-variation minimization","volume":"62","author":"Wang","year":"2013","journal-title":"Acta Phys. Sin."},{"issue":"5","key":"10.1016\/j.neucom.2019.09.087_bib0024","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1364\/JOSAA.31.000981","article-title":"Few-view image reconstruction with fractional-order total variation","volume":"31","author":"Zhang","year":"2014","journal-title":"J. Opt. Soc. Am. A Opt. Image Sci. Vis."},{"issue":"6","key":"10.1016\/j.neucom.2019.09.087_bib0025","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1088\/0031-9155\/56\/6\/003","article-title":"Improved total variation-based CT image reconstruction applied to clinical data","volume":"56","author":"Ludwig","year":"2011","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.neucom.2019.09.087_bib0026","series-title":"Proceedings of the 2014 IEEE Nuclear Science Symposium and Medical Imaging Conference","first-page":"1","article-title":"Prior image based anisotropic edge guided TV minimization for few-view CT reconstruction","author":"Rong","year":"2014"},{"key":"10.1016\/j.neucom.2019.09.087_bib0027","doi-asserted-by":"crossref","DOI":"10.1155\/2016\/3094698","article-title":"An improved total variation minimization method using prior images and Split\u2013Bregman method in CT reconstruction","volume":"2016","author":"Deng","year":"2016","journal-title":"Biomed. Res. Int."},{"issue":"12","key":"10.1016\/j.neucom.2019.09.087_bib0028","doi-asserted-by":"crossref","first-page":"2997","DOI":"10.1088\/0031-9155\/59\/12\/2997","article-title":"Sparse-view X-ray CT reconstruction via total generalized variation regularization","volume":"59","author":"Niu","year":"2014","journal-title":"Phys. Med. Biol."},{"key":"10.1016\/j.neucom.2019.09.087_bib0029","doi-asserted-by":"crossref","first-page":"64225","DOI":"10.1109\/ACCESS.2018.2873713","article-title":"Adaptive weighted total variation minimization based alternating direction method of multipliers for limited angle CT reconstruction","volume":"6","author":"Luo","year":"2018","journal-title":"IEEE Access"},{"issue":"9","key":"10.1016\/j.neucom.2019.09.087_bib0030","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. Imaging"},{"issue":"1","key":"10.1016\/j.neucom.2019.09.087_bib0031","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1109\/TMI.2016.2600249","article-title":"Tensor-based dictionary learning for spectral CT reconstruction","volume":"36","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"1","key":"10.1016\/j.neucom.2019.09.087_bib0032","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1088\/0031-9155\/57\/1\/173","article-title":"Fair-view image reconstruction with dual dictionaries","volume":"57","author":"Lu","year":"2012","journal-title":"Phys. Med. Biol."},{"issue":"8","key":"10.1016\/j.neucom.2019.09.087_bib0033","doi-asserted-by":"crossref","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","article-title":"Image denoising by sparse 3-D transform-domain collaborative filtering","volume":"16","author":"Dabov","year":"2007","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2019.09.087_bib0034","doi-asserted-by":"crossref","first-page":"175","DOI":"10.5201\/ipol.2012.l-bm3d","article-title":"An analysis and implementation of the BM3D image denoising method","volume":"2","author":"Lebrun","year":"2012","journal-title":"Image Process. Line"},{"key":"10.1016\/j.neucom.2019.09.087_bib0035","first-page":"1470","article-title":"Fast high-dimensional bilateral and nonlocal means filtering","volume":"1","author":"Nair","year":"2018","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"10.1016\/j.neucom.2019.09.087_bib0036","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1109\/TIP.2018.2869685","article-title":"Statistical nearest neighbors for image denoising","volume":"28","author":"Frosio","year":"2019","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2019.09.087_bib0037","doi-asserted-by":"crossref","first-page":"412","DOI":"10.1016\/j.neucom.2018.10.023","article-title":"Low-rank Bayesian tensor factorization for hyperspectral image denoising","volume":"331","author":"Wei","year":"2019","journal-title":"Neurocomputing"},{"issue":"1","key":"10.1016\/j.neucom.2019.09.087_bib0038","doi-asserted-by":"crossref","DOI":"10.1088\/1674-1137\/41\/1\/017003","article-title":"Optimized feed-forward neural-network algorithm trained for cyclotron-cavity modeling","volume":"41","author":"Mohamadian","year":"2017","journal-title":"Chin. Phys. C"},{"key":"10.1016\/j.neucom.2019.09.087_bib0039","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.neucom.2018.08.034","article-title":"Hybrid no-propagation learning for multilayer neural networks","volume":"321","author":"Adhikari","year":"2018","journal-title":"Neurocomputing"},{"issue":"12","key":"10.1016\/j.neucom.2019.09.087_bib0040","doi-asserted-by":"crossref","first-page":"5659","DOI":"10.1109\/TIP.2015.2487860","article-title":"Multimodal deep autoencoder for human pose recovery","volume":"24","author":"Hong","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2019.09.087_bib0041","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.neucom.2018.11.028","article-title":"Vector-kernel convolutional neural networks","volume":"330","author":"Ou","year":"2019","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2019.09.087_bib0042","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.neucom.2018.08.075","article-title":"Balance gate controlled deep neural network","volume":"320","author":"Liu","year":"2018","journal-title":"Neurocomputing"},{"key":"10.1016\/j.neucom.2019.09.087_bib0043","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1016\/j.neucom.2018.12.075","article-title":"Dilated residual networks with symmetric skip connection for image denoising","volume":"345","author":"Peng","year":"2019","journal-title":"Neurocomputing"},{"issue":"7","key":"10.1016\/j.neucom.2019.09.087_bib0044","doi-asserted-by":"crossref","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","article-title":"Beyond a Gaussian denoiser: residual learning of deep CNN for image denoising","volume":"26","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.neucom.2019.09.087_bib0045","series-title":"Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"21","article-title":"Learning fully convolutional networks for iterative non-blind deconvolution","author":"Zhang","year":"2017"},{"key":"10.1016\/j.neucom.2019.09.087_bib0046","article-title":"View-interpolation of sparsely sampled sinogram using convolutional neural network","volume":"10133","author":"Lee","year":"2017","journal-title":"SPIE Med. Imaging"},{"key":"10.1016\/j.neucom.2019.09.087_bib0047","first-page":"1","article-title":"Spatial pyramid-enhanced NetVLAD with weighted triplet loss for place recognition","volume":"99","author":"Yu","year":"2019","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"5","key":"10.1016\/j.neucom.2019.09.087_bib0048","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIP.2018.2804218","article-title":"Local deep-feature alignment for unsupervised dimension reduction","volume":"27","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Image Process."},{"issue":"10","key":"10.1016\/j.neucom.2019.09.087_bib0049","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1002\/mp.12344","article-title":"A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction","volume":"44","author":"Kang","year":"2017","journal-title":"Med. Phys."},{"issue":"2","key":"10.1016\/j.neucom.2019.09.087_bib0050","doi-asserted-by":"crossref","first-page":"679","DOI":"10.1364\/BOE.8.000679","article-title":"Low-dose CT via convolutional neural network","volume":"8","author":"Chen","year":"2017","journal-title":"Biomed. Opt. Exp."},{"issue":"1","key":"10.1016\/j.neucom.2019.09.087_bib0051","doi-asserted-by":"crossref","first-page":"107","DOI":"10.1118\/1.1455742","article-title":"Principles of computerized tomographic imaging","volume":"29","author":"Kak","year":"2002","journal-title":"Med. Phys."},{"issue":"11","key":"10.1016\/j.neucom.2019.09.087_bib0052","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/j.neucom.2010.09.025","article-title":"Regularizers for fault tolerant multilayer feedforward networks","volume":"74","author":"Mak","year":"2011","journal-title":"Neurocomputing"},{"issue":"6","key":"10.1016\/j.neucom.2019.09.087_bib0053","doi-asserted-by":"crossref","first-page":"1407","DOI":"10.1109\/TMI.2018.2823338","article-title":"A sparse-view CT reconstruction method based on combination of densenet and deconvolution","volume":"37","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Med Imaging"},{"key":"10.1016\/j.neucom.2019.09.087_bib0054","series-title":"Proceedings of the International Conference for Learning Representations","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2015"},{"issue":"3","key":"10.1016\/j.neucom.2019.09.087_bib0055","doi-asserted-by":"crossref","first-page":"707","DOI":"10.1109\/TMI.2016.2627004","article-title":"Comparison between pre-log and post-log statistical models in ultra-low-dose CT reconstruction","volume":"36","author":"Fu","year":"2017","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10.1016\/j.neucom.2019.09.087_bib0056","series-title":"Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","article-title":"Learning deep CNN denoiser prior for image restoration","author":"Zhang","year":"2017"},{"key":"10.1016\/j.neucom.2019.09.087_bib0057","series-title":"Proceedings of the 23rd Annual ACM Conference on Multimedia Conference","first-page":"689","article-title":"Matconvnet: convolutional neural networks for matlab","author":"Vedaldi","year":"2015"},{"issue":"4","key":"10.1016\/j.neucom.2019.09.087_bib0058","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: from error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"10.1016\/j.neucom.2019.09.087_bib0059","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1088\/0031-9155\/60\/5\/1965","article-title":"Iterative CBCT reconstruction using Hessian penalty","volume":"60","author":"Sun","year":"2015","journal-title":"Phys. Med. Biol."},{"issue":"1","key":"10.1016\/j.neucom.2019.09.087_bib0060","doi-asserted-by":"crossref","first-page":"6700","DOI":"10.1038\/s41598-018-25153-w","article-title":"Artifact removal using improved googlenet for sparse-view CT reconstruction","volume":"8","author":"Xie","year":"2018","journal-title":"Sci. Rep."}],"container-title":["Neurocomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231219313967?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0925231219313967?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2020,1,8]],"date-time":"2020-01-08T12:28:55Z","timestamp":1578486535000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0925231219313967"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,2]]},"references-count":60,"alternative-id":["S0925231219313967"],"URL":"https:\/\/doi.org\/10.1016\/j.neucom.2019.09.087","relation":{},"ISSN":["0925-2312"],"issn-type":[{"value":"0925-2312","type":"print"}],"subject":[],"published":{"date-parts":[[2020,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Streaking artifacts suppression for cone-beam computed tomography with the residual learning in neural network","name":"articletitle","label":"Article Title"},{"value":"Neurocomputing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.neucom.2019.09.087","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2019 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}