The axon radius is a main determinant of the conduction velocity of action potentials. Robust, MRI-based axon radius estimation is sensitive to a tail-weighted estimate of the ensemble-average axon radius, i.e., the effective axon radius ($$$r_{\text{eff}}$$$). It is unclear how $$$r_{\text{eff}}$$$ translates into the arithmetic mean axon radius ($$$r_{\text{arith}}$$$), which may be more indicative of the conduction velocity than $$$r_{\text{eff}}$$$. We investigate the feasibility to predict $$$r_{\text{arith}}$$$ from $$$r_{\text{eff}}$$$ using linear regression on high-resolution, large-scale light-microscopy images of a human corpus callosum sample and validate this linear relationship with microscopy and diffusion-weighted MRI images of another human corpus callosum sample.
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