Active Contour-Based Analysis of Stent Characterization in Cardiac Coronary Arteries from 2D Intravascular Ultrasound Images

According to the World Health Organization, there are 17 million deaths from heart failure worldwide, with 8.7 million, or 31%, of them being caused by coronary heart disease. This disease occurs when the coronary arteries are blocked by a buildup of fat, which can lead to heart failure. One way to cure this disease is to perform stent surgery. To prevent more severe symptoms, early diagnosis and monitoring after stenting surgery are needed. To help physicians determine the diagnosis of this disease, a modality that reduces the risk to patients used in this study, the malposition of the stent. Images are created via Intra Vascular Ultrasound (IVUS) using ultrasound waves. Because of its non-invasive, real-time, and inexpensive nature, ultrasound imaging has several advantages over other imaging processes in the medical field, Ultrasound can produce excellent image quality. Doctors can also take advantage of ultrasound imaging to evaluate disease and reduce the higher risk of disease. However, the ultrasound image output still has drawbacks, one of which is the crackling sound which reduces the quality of the results, especially for images with low contrast. There are several methods that can be used to reduce the resulting noise; in this study, the Median Filter and Mn Filter methods are used; the Canny Edge Detector method is used to obtain the boundaries of the edges and contours of the heart artery images generated by the filter; and Active Contour, which adds features for measuring stent radius and area. Evaluation methods such as Mean Square Error (MSE), Signal to Noise Ratio (SNR), and Peak Signal to Noise Ratio (PSNR) are used in this study. The results showed that the software can characterize the stent, which makes the stent contour clearer and easier for the doctor to see, so that the doctor can make a diagnosis more easily.