Non-Cartesian Compressed Sensing for Diffusion Spectrum Imaging

INTRODUCTION: One important limitation of DTI is its inability to resolve multiple crossing fibers within a voxel. Diffusion Spectrum Imaging (DSI) allows such resolution by Nyquist sampling a 3D q-space[1] for each voxel. The water displacement probability (“propagator”) corresponds to the Fourier transform of the MR signal as a function of q r . This high dimensionality imposes a trade-off between resolution in diffusion space and scan time. It has been proposed [2,3] to accelerate DSI through the application of compressed sensing (CS)[4] in the three q-space dimensions. Rather than sampling a subset of a Cartesian q-space, we propose to further minimize coherent aliasing by undersampling q-space according to a non-Cartesian sampling pattern.