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lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain

Authors :
Farshid eSepehrband
Jeiran eChoupan
Emmanuel eCaruyer
Nyoman Dana Kurniawan
Yaniv eGal
Quang M Tieng
Katie eMcMahon
Viktor eVegh
David C Reutens
Zhengyi eYang
Centre for Advanced Imaging
University of Queensland [Brisbane]
Queensland Brain Institute
Section for Biomedical Image Analysis (SBIA)
Perelman School of Medicine
University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia]
School of Information Technology and Electrical Engineering [Brisbane]
Source :
Frontiers in Neurology, Frontiers in Neurology, Frontiers, 2015, 5 (290), ⟨10.3389/fneur.2014.00290⟩, Frontiers in Neurology, Vol 5 (2015)
Publication Year :
2015
Publisher :
Frontiers Media S.A., 2015.

Abstract

International audience; We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

Details

Language :
English
ISSN :
16642295
Volume :
5
Database :
OpenAIRE
Journal :
Frontiers in Neurology
Accession number :
edsair.doi.dedup.....ad9cd0a03bdff686d79e8ed417b4ba85
Full Text :
https://doi.org/10.3389/fneur.2014.00290