This study aimed to generate myocardial perfusion images from coronary angiography (CAG) using Patlak plot analysis and evaluate their effectiveness in detecting ischemia. Data from 29 patients were analyzed. Electrocardiogram-synchronized CAG images of the left coronary artery were registered and processed for pixel-wise Patlak analysis. Image generation succeeded in 18 cases (62%) and failed in 11 due to motion artifacts caused by irregular heartbeats, table panning, or deep breathing. The resulting images clearly distinguished ischemic from normal regions. Perfusion values were significantly lower in ischemic regions compared to normal regions (p < 0.001). Despite technical challenges and variability in patient conditions, this method enabled consistent identification of perfusion deficits. Enhancing image processing increases the success rate. This approach allows ischemia assessment directly from CAG data and supports timely treatment planning, contributing to improved diagnostic precision and clinical decision-making in selected cases.