Abstract #2053

Real valued diffusion weighted imaging using decorrelated phase filtering

Tim Sprenger Sprenger^1,2, Jonathan I. Sperl², Brice Fernandez³, Axel Haase¹, and Marion Menzel²

¹Technische Universität München, Munich, Germany, ²GE Global Research, Munich, Germany, ³GE Healthcare, Munich, Germany

Due to the intrinsic low signal to noise ratio in diffusion weighted imaging (DWI), magnitude processing often results in an overestimation of the signal’s amplitude. This results in low estimation accuracy of diffusion models and reduced contrast because of a superposition of the image signal and the noise floor. We adopt a new phase correction (PC) technique yielding real valued data and maintaining a Gaussian noise distribution. The advantage of PC is shown in a DSI experiment where the Ensemble average propagator is better delineated in the real valued data and delineation improves as the noise floor is lowered.

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