Neuroimaging data is best represented in three-dimensional form, due to its implicit spatial content. Hence, bar graphs or other common 2D statistical tools for neuroimaging data often hinder spatial understanding and require additional resources for complete data representation. A more intuitive way to visualize neuroimaging data is therefore through a 3D brain model, with regions of higher correspondence darker in color than other regions. Overall, this study aims to build a full-stack web application to help Penn Medicine epilepsy patients visualize their brain data in 3D form, using technologies such as React.js, Node.js, Express.js, Blender, and Python. 

In terms of the web application itself, after the upload of a Comma-Separated Values file (CSV) of numbers and the selection of both color and brain map (atlas), the user can view the three-dimensional result of mapping the values of the CSV file to each region in the selected brain atlas. To clarify, each brain region of this final model will be darker or lighter in shade depending on the color chosen and the value mapped to that region (as inputted from the CSV file). Thus, depending on the shade of the color, users see which brain region had higher or lower values of correspondence, channeling understanding of the brain data.

This web application is developed mainly using React.js, Node.js, Express.js, Python, and Blender framework. Specifically, the user interface (or front-end) is developed primarily in React.js. Upon successful submission of each user input, a HTTP request is thrown to the Express.js server within Node.Js. Finally, upon submission of the Run Python button, a HTTP request exacts a main python script that internally runs Blender in the background, creating and exporting a final 3D Model that adheres to the user’s latest inputted CSV file, color, and atlas. When the python script terminates, the virtual React DOM would update itself to the latest brain model, allowing the user to successfully visualize their neuroimaging data in three-dimensional form.