Angiographic images modeling and processing of coronary artery disease patients in order to determine coronary artery stenosis

Background: Advances in computer science have led to the emergence of existing cardiovascularassessment tools. CTA (computed tomography angiography) is an imaging method for visualizingarterial and venous vessels throughout the body, which is widely used today. Clinical evaluationsmainly rely on visual evaluation or manual measurement by cardiologists, which are naturally notfree from human errors. On the other hand, due to the increase in mortality due to cardiovasculardiseases and its significant growth as the first cause of death in Iran, the study and prevention ofthis disease has a high priority. Among cardiovascular diseases, coronary artery disease is themost important and the main cause of heart attacks. The aim of this research is to implement imageprocessing techniques on coronary angiography images to automatically detect the degree ofcoronary artery occlusion.Methods: The process of current research includes: ۱- Preprocessing (Image reprocessing), ۲-Image Enhancement, ۳- Separation of coronary vessels (Image Segmentation), ۴- Centerline Extractionand diameter calculation, ۵- Stenosis Detection, ۶- Evaluation of system performance andaccuracyResults: Image processing and modeling results, high performance to detect the degree of coronaryartery occlusion and can be used as a second opinion for experts.Discussion: In this research, the processing of coronary angiography images, resulted a highperformance model to automatically detect the degree of coronary artery occlusion. As the nextprocess, due to increasing the usability of model, Establishment of a decision support system(DSS), should be considered.