Accurate polyp size measurements are essential for risk stratification, selection of polypectomy techniques, and surveillance interval assignments. Evidence indicated that the clinical implementation of artificial intelligence is an optimal tool to improve the measurement of polyps during colonoscopy. This study aimed to evaluate the performance of a computer-aided measuring (CAM) system (EndoDASS) and compare its accuracy with routine sizing methods during real-time colonoscopy.