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

Farshid Sepehrband 1, 2 Jeiran Choupan 1, 2 Emmanuel Caruyer 3 Nyoman Kurniawan 1 Yaniv Gal 4 Quang Tieng 1 Katie L. Mcmahon 1 Viktor Vegh 1 David Reutens 1 Yang Zhengyi 1, 4
1 Centre for Advanced Imaging
2 Queensland Brain Institute
3 SBIA - Section for Biomedical Image Analysis
4 School of Information Technology and Electrical Engineering
Abstract : 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.
Keywords : signal processing on the sphere filtering acquisition design diffusion MRI
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Article dans une revue
Frontiers in Neurology, Frontiers, 2015, 5 (290), 〈10.3389/fneur.2014.00290〉
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Farshid Sepehrband, Jeiran Choupan, Emmanuel Caruyer, Nyoman Kurniawan, Yaniv Gal, et al.. lop-DWI: A Novel Scheme for Pre-Processing of Diffusion Weighted Images in the Gradient Direction Domain. Frontiers in Neurology, Frontiers, 2015, 5 (290), 〈10.3389/fneur.2014.00290〉. 〈hal-01103577〉

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