Robustness of Phase Sensitive Reconstruction in Diffusion Spectrum Imaging
Marion I Menzel 1 , Tim Sprenger 1,2 , Ek T Tan 3 , Valdimir Golkov 1,2 , Christopher J Hardy 3 , Luca Marinelli 3 , and Jonathan I Sperl 1
Diagnostics, Imaging and Biomedical
Technologies Europe, GE Global Research, Munich,
University Munich, Munich, Germany,
Global Research, Niskayuna, NY, United States
Common diffusion MRI data processing is based on the
magnitude, neglecting any phase in the underlying DWI.
The observed net phase has a variety of contributing
sources (B0 inhomogeneity, eddy currents, motion, etc.)
which are difficult to disentangle. Separating these
phase contributions however is advantageous, as the
phase contains information on coherent motion (i.e.
brain pulsatility); and as processing of DWI to obtain
parametric quantities like DTI and Kurtosis benefits
from taking real valued data, as magnitude processing
introduces Rician bias. This work examines robustness of
phase sensitive reconstruction applied to DSI data in
phantoms and in vivo human brain.
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