Computational frameworks for multi-fascicle models: impact on microstructural descriptors

When performing operations on multi-fascicle DCI models, the need to preserve microstructural descriptors such as fFA and fMD is important. In this work we compared different multi-fascicle computational frameworks by assessing their impact on microstructure properties. Specifically, we investigated the impact after geometrical transformation and averaging of multi-fascicle models, two key operations when carrying out population studies. We found that Euclidean and log-Euclidean frameworks resulted in a decrease of fFA and fMD. More surprisingly, the values of microstructural descriptors depended on the number of subjects. The quaternion framework, in contrast, was the best at preserving microstructural features.