Phase Recognition in Coronary Angiography Procedures: A Random Forest Approach Using Video and C-Arm System Logging Data

This thesis investigates clinical phase recognition for cardiac catheterization purposes, focusing on coronary angiography (CAG) procedures, in the context of an increasing annual prevalence of coronary artery disease. It applies machine learning to analyze C-arm logs and video recordings, aiming to improve procedural efficiency by recognizing...