The goal of this project is to develop methods for identification, extraction, tracking, and comparison of topological descriptors in the time-varying data. Thereby the focus is on applying these methods to dynamic networks, 3D volumetric, scalar, or vector fields. In a first example, fMRI data along with clinical parameters is considered, which has been acquired to get a better understanding of changes in brain network topology and their relationship with clinical parameters or better performance (e.g anxiety, depression, better in solving math tasks, etc). Topological distance measures are proposed to analyze and compare the extracted topological features to better understand the data. For this purpose, correspondence problem may use to calculate the distance between these topological descriptors.
Contact: Farhan Rasheed