Diffusion Magnetic Resonance Imaging is a state-of-the-art technique that can provide accurate identification of complex neuronal fiber configurations in the human brain. Typical acquisition times are however too long for the clinical application. We propose a method to recover the fiber orientation distribution (FOD) at high spatio-angular resolution via practical kq-space under-sampling patterns that enable both acceleration and super-resolution. The inverse problem for FOD reconstruction is regularized by a structured sparsity prior promoting simultaneously voxelwise sparsity and spatial smoothness of fiber orientations. A convex minimization problem is formulated and solved via a forward-backward algorithm. Real data analysis suggest that high spatio-angular resolution FOD mapping can be achieved from severe kq-space acceleration.
|Title of host publication||2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)|
|Publication status||Published - 5 Mar 2020|
|Event||8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing 2019 - Le Gosier, Le Gosier, Guadeloupe|
Duration: 15 Dec 2019 → 18 Dec 2019
|Conference||8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing 2019|
|Abbreviated title||CAMSAP 2019|
|Period||15/12/19 → 18/12/19|