Semi-Automated Microbleed Identification on Susceptibility Weighted Images

Samuel Barnes^1,2, E. Mark Haacke¹

A method to detect microbleeds in the brain in a semi-automated fashion is presented. The goal of this technique is to reduce the processing time of quantifying microbleeds. The semi-automated method compares favorably with manual counting achieving approximately 80% sensitivity and 100% specificity while reducing processing time to under an hour.