Diffusion‐weighted (DW) magnetic resonance imaging (MRI) can provide unique insights into the microstructure of living tissue and is increasingly used to study the microanatomy and development of normal functioning tissue as well as its pathology. Mathematical models for analysis and interpretation have been crucial for the development and translation of DW‐MRI. Even though diffusion tensor imaging (DTI),1 which is based on a simple Gaussian model of the DW‐MRI signal, has shown promise in clinical applications,2 e.g. Alzheimer's disease,3 multiple sclerosis4 or brain tumors,5 a much wider variety of DW‐MRI models has been proposed to extract more information from the DW signal.