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

• Main Authors: Farshid eSepehrband, Jeiran eChoupan, Emmanuel eCaruyer, Nyoman Dana Kurniawan, Yaniv eGal, Quang M Tieng, Katie eMcMahon, Viktor eVegh, David C Reutens, Zhengyi eYang
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2015-01-01
• Series: Frontiers in Neurology
• Subjects: HARDI; Diffusion Weighted Imaging; pre-processing; Local reconstruction; gradient direction domain; Spiral sampling
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fneur.2014.00290/full

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 fibre 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 fibre tracks was significantly improved using our method.