3D Visualization of iEEG: An Automated Pipeline


Engineering and Applied Sciences


Assistant Professor of Neurology

Project Summary

This summer, I worked at the Centre for Neuroengineering and Therapeutics in Hayden Hall on automating a pipeline that creates 3D visualizations for iEEG.
Intracranial electroencephalography (iEEG) is an invasive technique that uses implanted electrodes to record brain activity. It is commonly used in the diagnosis and treatment of drug-resistant epilepsy, specifically by recording electrical activity around a seizure period to localize a seizure’s onset and network. The original viewer takes cortical meshes, electrode contact names and coordinates, and the MRI-CT fusion matrix/images for a particular patient to render an interactive web model through Blender and its add-on, Blend4Web. However, the process requires stepwise manual interaction, which is time-consuming and can be difficult for those who are unfamiliar with Unix and/or the multiple software tools employed. 
To mitigate these challenges, I created a shell script for Unix systems that automates the processing pipeline from inputs to website, with the goals of streamlining the process and removing it from human supervision, and making it more organized and accessible. The script, freesurfer2web.sh, has two parts: (1) processing of the surface files and electrode coordinates, and (2) creating the web visualization with Blender + Blend4Web. When run inside a subject's directory, the script will automatically return a .json file that can be modified through JavaScript to create the finished webpage. Although there still remains multiple area of improvement, the project ultimately aims to provide a foundation for an efficient, open-source, and user-friendly tool that can be used to create robust 3D visualizations for use in an array of clinical and research settings.
Although short-term, this project was an enjoyable, hands-on way to learn about brain visualization as well as the clinical applications of iEEG and engineering research. I was able to gain exposure to many different areas the lab was involved in as well during my time there (e.g. network neuroscience, imaging, machine learning) as well as become more familiar with a variety of programming languages (R, MATLAB, Unix and Python). Aside from the project, I was also able to participate in a diverse range of activities, such as shadowing in Radiology, surgical conferences in Neurology, and imaging meetings in Richards. Through them, I was able to get a glimpse into careers that are at the intersection of medicine and engineering, which was fascinating. I really enjoyed how varied my experience was, probably due to the size of CN&T and the number of different projects that go on at once. 
This summer was a great experience for me and I am happy I decided to stay in Philadelphia. I was able to meet great mentors, gain experience to current trends in neuroscientific research, as well as get to know the city better. I am extremely grateful for the direction I ended up going, and my experience ultimately provided me with new insights into my interests and future career goals.