Abstract #2945

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

Miguel Molina-Romero ^1,2 , Jonathan I. Sperl ² , Tim Sprenger ^1,2 , Pedro A. Gmez ^1,2 , Xin Liu ^1,2 , Ek T. Tan ³ , Christopher J. Hardy ³ , Luca Marinelli ³ , Bjoern Menze ¹ , Derek K. Jones ⁴ , and Marion I. Menzel ²

¹ Technical University Munich, Garching, BY, Germany, ² GE Global Research, Garching, BY, Germany, ³ GE Global Research, Niskayuna, NY, United States, ⁴ Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, United Kingdom

Varying the diffusion mixing time ( Capital Greek Delta

) in a Stejskal-Tanner experiment allows one to obtain information about the tissue microstructure. These experiments require either high-gradient-field scanners, long scanning times, or prior knowledge of the fiber orientation. 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 Capital Greek Delta

is clinically not feasible in terms of measuring time. Therefore, we need a technique that allows combining DSI acquisition and different Capital Greek Delta

in clinical time. In this abstract, we present a compressed sensing algorithm and a study of five different denoising associated techniques that reduce the measuring time up to a factor of R=4.

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