Keywords: Data Processing, Data ProcessingWe estimated biophysical model parameters using a dictionary of diffusion signals. The dictionary is generated based on the set of biophysical model parameters. We then rotated this dictionary along fascicle direction derived from spherical deconvolution and tried to fit it to the diffusion signal using non-negative linear least square optimization to find the associated dictionary weights. These weights went through a deep learning network to find model parameters. Our approach shows reasonable accuracy and reliability for biophysical model estimation. It is also possible to extend our approach to more complex and general biophysical models to achieve higher specificity.
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