Conceptual Framework For Optimized Pipeline Selection For Brain Tractography Using Multi-Criteria Decision Analysis

Abstract

Diffusion Tensor Imaging (DTI) allows us to reconstruct the brain white matter (WM) pathways in-vivo. Generating a diffusion tractograph from raw MRI data involves multiple layers of processes. Each set of processes that produces a particular analysis is called a pipeline. An extensive collection of software tools have been developed over the years for each layer of tractograph generation, giving researchers the freedom to choose the tools of their preference for different processes. However, this has resulted in the establishment of various pipelines aimed towards the same task, and depending upon an analysis, one pipeline may be more suitable than the other. This creates a hurdle for the clinical application of the DTI tools, as the clinicians and neuroscience researchers are not usually conversant with the technical aspects of the DTI tools. This study proposes an automated decision model for selection of tractography pipelines that will allow researchers and clinicians to select best of the possible DTI pipelines for a particular Analysis.