Objectives Even in the presence of physical indicators like pain, tumor, color, and function loss, determining the exact size or location of acute dental apical diseases is challenging. Even harder to detect is chronic apical periodontitis, which is asymptomatic. In such circumstances, use of dental radiography is especially beneficial. However, radiographs are not sufficient by themselves, and require interpretation by a well-trained dental specialist. Nevertheless, owing to the human factor, mistakes leading to incorrect treatment can be made by specialists because of a wrong diagnosis. This study aimed to introduce an automated dental apical lesion detection methodology by assessing changes in hard tissue structures. The system consists of modules for jaw separation, tooth segmentation, root localization, and lesion detection.