Sylvain Louis Merlet1, Michael Paquette2, Rachid Deriche3, Maxime Descoteaux2
1Athena Project-Team, INRIA, Sophia Antipolis , Mditerrane, France; 2Computer Science Departement, Universit de Sherbrooke, Qubec, Canada; 3Athena Project-Team, INRIA, Sophia Antipolis, Mditerrane, France
Sparsity is one of the key ingredient in Compressed Sensing recovery. In Diffusion MRI, few studies have been proposed to characterize the sparsity of the Ensemble Average Propagator which captures the water diffusion phenomenon. We propose a fair comparison of two classes of representations : The discrete representations, via the Haar, Daubechie-Cohen-Fauveau (DCF) 5-3, DCF 9-7 wavelets bases, and the continuous representations, via Spherical Polar Fourier (SPF) and 3D Simple Harmonic Oscillation Reconstruction and Estimation (SHORE) bases. We study the advantages and disadvantages of these discrete and continuous representations EAP for the first time.