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

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 no...

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Bibliographic Details
Published in:Frontiers in neurology 2015, Vol.5 (290), p.290-290
Main Authors: Sepehrband, Farshid, Choupan, Jeiran, Caruyer, Emmanuel, Kurniawan, Nyoman D, Gal, Yaniv, Tieng, Quang M, McMahon, Katie L, Vegh, Viktor, Reutens, David C, Yang, Zhengyi
Format: Article
Language:English
Subjects:
Computer Science
Diffusion Weighted Imaging
gradient direction domain
HARDI
Local reconstruction
Medical Imaging
Neuroscience
pre-processing
Spiral sampling
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Summary: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.
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2014.00290