Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial IntelligenceFree water imaging (FWl), among the diffusion MRI (dMRI) family, is an extended version of the single diffusion tensor model by adding the isotropic diffusion compartment. Generally, FWI parameters have been estimated by fitting of signal model to measured DWI signals. Recently, machine learning techniques have shown promising results also in dMRI parameter inference.In this study, we aimed at development of a hybrid approach for FWI parameter estimation based on synthetic q-space learning (synQSL) and conventional fitting.Our approach was validated by comparison with the conventional fitting method based on quantitative and visual evaluation and computation time.
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