As a PhD Graduate Research Assistant under John Shepherd PhD, I conduct imaging research which is primarily focused on breast cancer. Our research group seeks to discover novel imaging bio-markers to detect cancer and asses risk. Machine and deep learning are big components of my research as it is a powerful tool for analyzing high dimensionality data that is images. My background in high performance computing and software engineering allows me to fully leverage our GPU clusters to rapidly build and train machine learning models.
Breast Thickness Tomosynthesis - Breast density is a biomarker that is associated with cancer risk. Accurate point thickness measurements of the breast are necessary for calculating density. We use nine views from a sinogram to solve and inverse problem and derive point thickness measurements.