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Abstract #4753

Single-Shell Free Water Imaging by Synthetic Q-Space Learning

Yoshitaka Masutani1 and Koh Sasaki1,2
1Graduate School of Information Sciences, Hiroshima City University, Hiroshima, Japan, 2Hiroshima Heiwa Clinic, Hiroshima, Japan


Free water imaging (FWI) belongs to the dMRI family, and is an extention of the DTI model by adding the isotropic diffusion compartment. Conventionally, FWI parameters have been obtained by numerical fitting to measured signal values of DWI of single-shell or multi-shell. It has been reported that it is harder to obtain robust results in single shell data. Recently, machine learning techniques have shown promising results in dMRI parameter inference. In this study, we aimed at FWI parameter inference from single-shall dMRI data by using synthetic Q-space learning. Several validation experiments by quantitative and visual assessments were performed.

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