Current Research

Identification and Quantitative Analysis of Intracerebral Hemorrhages via Machine Learning Techniques

Developed a machine learning model which can, off of MR-images, identify and segment anatomical elements of an intracerebral hemorrhage, and perform volumetric analyses to estimate respective volumes of hematoma and peripheral edema. The intention is to use this model for real-time image guidance during surgical evacuations of intracerebral hemorrhages.