Traditionally, MRI data sets only include a small number of subjects and can be analyzed on a personal computer. But as we look towards a future where “Big Data” is playing a larger role in scientific discovery, and large, publicly available MRI data sets are being aggregated across laboratories, new tools will be needed for analyzing and exploring these data. Ariel Rokem, Adam Richie-Halford, Josh Smith and Jason Yeatman have been working on developing a new, web browser-based graphical user interface for exploring diffusion MRI and tractography data sets. AFQ-Browser provides an easy way to visualize diffusion data for different fiber tracts, explore and individual’s brain anatomy, examine group comparisons, or identify individuals that are substantially different from the other subjects. The vision for this project is to develop a tool that capitalizes on web browser technology to support the analysis of neuroimaging Big Data in the cloud. We are beginning to work on v0.2, and we welcome feedback and/or contributions over github regarding bugs that you uncover or useful features that you would like us to consider. Here is a link to a running instance with example data, and here is a link to the github repository with code and documentation.

AFQ-Browser is a Python package, and can be easily installed using pip (pip install AFQ-Browser), and is fully compatible with the current, MATLAB implementation of AFQ.