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