Comparison of different compressed sensing denoising strategies for DSI acquisition for several diffusion mixing times

Varying the diffusion mixing time in a Stejskal-Tanner experiment allows one to obtain information about the tissue microstructure organization. These types of experiments require either high-gradient-field scanners, scanning times on the order of days, or prior knowledge of the fiber orientation direction. Nevertheless, these problems can be solved while keeping the number of measurements under 120 with fixed maximum gradient strength. On the other hand, sampling the full q-space allows one to work with no model constraints in the propagator space and potentially might reveal further tissue information. However, a full DSI acquisition for a given set of more than one diffusion mixing time is clinically not feasible in terms of measuring time, since only one mixing acquisition time takes about 50 minutes (511 directions and 48 slices). Therefore, we need a technique that allows combining DSI acquisition and different diffusion mixing times while the measuring time is reduced or kept constant, as we increase the number of acquisitions in the mixing time direction. In this abstract, we expand the compressed sensing method presented in to the diffusion mixing time and study five different denoising algorithms for the compressed sensing problem.     «

Varying the diffusion mixing time in a Stejskal-Tanner experiment allows one to obtain information about the tissue microstructure organization. These types of experiments require either high-gradient-field scanners, scanning times on the order of days, or prior knowledge of the fiber orientation direction. Nevertheless, these problems can be solved while keeping the number of measurements under 120 with fixed maximum gradient strength. On the other hand, sampling the full q-space allows one to...     »