Abstract: Millions of individuals are affected by the atherosclerosis which is consider a prevalent disease and leading cause of death in the world also it can cause the coronary artery disease. Since, most of the images which took from X-ray angiographies have different kinds of artifacts such as non-uniform illumination, low contrast, so, the aim of this study is to increase the efficiency of medical segmentation images to provide an integrated diagnostic system that works to distinguish the atherosclerosis. To ensure the performance of the segmentation algorithm with respect to the quality of the input image data, a set of enhancement tasks have been applied to improve the clarity of the artery structure and localize the coronary artery grid. The sub-stages of pre-processing includes: enhancement, segmentation, hole/gaps removal. Also, a method for detection the atherosclerosis is proposed. The successful ration of proposed system was (98%) from artery segmentation stage and 95% for detection atherosclerosis.