Tensor denoising of multidimensional MRI data

Purpose To develop a denoising strategy leveraging redundancy in high‐dimensional data. Theory and Methods The SNR fundamentally limits the information accessible by MRI. This limitation has been addressed by a host of denoising techniques, recently including the so‐called MPPCA: principal component...

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Vydané v:	Magnetic resonance in medicine Ročník 89; číslo 3; s. 1160 - 1172
Hlavní autori:	Olesen, Jonas L., Ianus, Andrada, Østergaard, Leif, Shemesh, Noam, Jespersen, Sune N.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Wiley Subscription Services, Inc 01.03.2023 John Wiley and Sons Inc
Predmet:	Algorithms Blurring Brain - diagnostic imaging denoising diffusion Diffusion Magnetic Resonance Imaging - methods Magnetic resonance imaging Magnetic Resonance Imaging - methods Mathematical analysis Multidimensional data Noise reduction Patches (structures) Phantoms, Imaging Principal Component Analysis Principal components analysis random matrix theory Redundancy Signal-To-Noise Ratio s—Computer Processing and Modeling Tensors denoising random matrix theory diffusion principal component analysis
ISSN:	0740-3194, 1522-2594, 1522-2594
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