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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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