A Study on Preprocessing Techniques for Ultrasound Images of Carotid Artery

Ultrasound imaging has been widely used in the diagnosis of atherosclerosis. To precisely diagnose the carotid plaque, the affected region should be segmented from the ultrasonic image of carotid artery. Many techniques have been used to identify the plaque in ultrasound images. Image enhancement and restoration are the important processes to acquire high-quality images from the noisy images. When the artery images are captured, noise occurs due to high-frequency rate. To acquire a high-quality image, preprocessing is the first step to be done. The quality of the image is improved in this process. The techniques involved in preprocessing are dealt in this paper. Preprocessing involves filtering the image and removing the noise by various filtering techniques. Salt-and-pepper and Gaussian noise in ultrasound images can be filtered using techniques like mean, median and Wiener filters. Salt-and-pepper noise is multiplicative in nature and it is introduced by the image acquisition mechanism. The quality of the input sensor is reflected by the Gaussian noise. In this paper, the performance of image enhancement techniques on ultrasound images are evaluated using quality metrics, namely Mean Square Error (MSE) and Peak Signal–to-Noise Ratio (PSNR).