Denoising High-Field Multi-Dimensional MRI With Local Complex PCA.

Abstract:

:Modern high field and ultra high field magnetic resonance imaging (MRI) experiments routinely collect multi-dimensional data with high spatial resolution, whether multi-parametric structural, diffusion or functional MRI. While diffusion and functional imaging have benefited from recent advances in multi-dimensional signal analysis and denoising, structural MRI has remained untouched. In this work, we propose a denoising technique for multi-parametric quantitative MRI, combining a highly popular denoising method from diffusion imaging, over-complete local PCA, with a reconstruction of the complex-valued MR signal in order to define stable estimates of the noise in the decomposition. With this approach, we show signal to noise ratio (SNR) improvements in high resolution MRI without compromising the spatial accuracy or generating spurious perceptual boundaries.

journal_name

Front Neurosci

authors

Bazin PL,Alkemade A,van der Zwaag W,Caan M,Mulder M,Forstmann BU

doi

10.3389/fnins.2019.01066

subject

Has Abstract

pub_date

2019-10-09 00:00:00

pages

1066

eissn

1662-4548

issn

1662-453X

journal_volume

13

pub_type

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