Leveraging manifold learning techniques to explore white matter anomalies: An application of the TractLearn pipeline in epilepsy.

ABSTRACT: An accurate description of brain white matter anatomy in vivo remains a challenge. However, technical progress allows us to analyze structural variations in an increasingly sophisticated way. Current methods of processing diffusion MRI data now make it possible to correct some limiting biases. In addition, the development of statistical learning algorithms offers the opportunity to analyze the data from a new perspective. We applied newly developed tractography models to extract quantitative white matter parameters in a group of patients with chronic temporal lobe epilepsy. Furthermore, we implemented a statistical learning workflow optimized for the MRI diffusion data - the TractLearn pipeline - to model inter-individual variability and predict structural changes in patients. Finally, we

SUBMITTER: Roger E 

PROVIDER: S-EPMC9668609 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature