A Kernel-based Low-rank (KLR) Model for Low-dimensional Manifold Recovery in Highly Accelerated Dynamic MRI

While many low rank and sparsity based approaches have been developed for accelerated dynamic magnetic resonance imaging (dMRI), they all use low rankness or sparsity in input space, overlooking the intrinsic nonlinear correlation in most dMRI data. In this paper, we propose a kernel-based framework...

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Bibliographic Details
Published in:IEEE Trans Med Imaging
Main Authors: Nakarmi, Ukash, Wang, Yanhua, Lyu, Jingyuan, Liang, Dong, Ying, Leslie
Format: Artigo
Language:Inglês
Published: 2017
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Article
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC6422674/
https://ncbi.nlm.nih.gov/pubmed/28692970
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TMI.2017.2723871
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