Abstract
High spatio-angular resolution diffusion MRI (dMRI) has been shown to provide accurate identification of complex neuronal fiber configurations, albeit, at the cost of long acquisition times. We propose a method to recover intra-voxel fiber configurations at high spatio-angular resolution relying on a 3D kq-space under-sampling scheme to enable accelerated acquisitions. The inverse problem for the reconstruction of the fiber orientation distribution (FOD) is regularized by a structured sparsity prior promoting simultaneously voxel-wise sparsity and spatial smoothness of fiber orientation. Prior knowledge of the spatial distribution of white matter, gray matter, and cerebrospinal fluid is also leveraged. A minimization problem is formulated and solved via a stochastic forward–backward algorithm. Simulations and real data analysis suggest that accurate FOD mapping can be achieved from severe kq-space under-sampling regimes potentially enabling high spatio-angular resolution dMRI in the clinical setting.
Original language | English |
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Article number | 226 |
Journal | Journal of Imaging |
Volume | 7 |
Issue number | 11 |
Early online date | 27 Oct 2021 |
DOIs | |
Publication status | Published - Nov 2021 |
Keywords
- Compressed sensing
- Data acquisition
- Diffusion MRI
- HARDI
- Optimization
- Reconstruction
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design
- Electrical and Electronic Engineering