Diffusion magnetic resonance imaging of biological systems most often results in non-monoexponential signal, due to their complexity and heterogeneity. One approach to interpreting the data without imposing microstructural models is to fit it to a multiexponential function, and to display the coefficients as a distribution of the diffusivities. Here we suggest parameterizing the measured water mobility spectra using a bimodal lognormal function. This approach allows for a compact representation of the spectrum, while also resolving overlapping spectral peaks. We apply the method on a spinal cord sample and use it to generate robust intensity images of slow and fast-diffusion components.
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