OpenDIVE: Streamlining Tractography Visualization

Adam M. Saunders, Elyssa M. McMaster, Chris Rorden, Johaan Kathilankal Jis, Minyi Sun, Adam Sadriddinov, Lukas VanTilburg, Michael Eugene Kim, Bennett Allan Landman, Kurt Schilling

Keywords: Diffusion, tractography, visualization

TL;DR: We created a user-friendly Python tool to visualize diffusion MRI summary statistics over regions of interest.

Abstract:

Diffusion-weighted magnetic resonance imaging (DW-MRI) models provide a non-invasive
method for mapping the structure of white matter. Despite the prolific availability of soft-
ware tools to visualize DW-MRI, an MRI acquisition technique with increasing prevalence
in deep learning applications, mapping meaningful summary statistics of white matter re-
lationships can be a time-consuming process. We propose a Python-based command line
tool to both standardize and improve accessibility to white matter models. We generate a
standardized display of anatomical images to overlay diffusion models based on user input,
and we provide a mechanism to display summary statistics (percent change, p-value, deep
learning metrics, etc.) with a changeable color bar.

Submission Number: 33