EFFICIENT ANALYSIS OF MEDICAL IMAGE DE-NOISING FOR MRI AND ULTRASOUND IMAGES

Magnetic resonance imaging (MRI) and ultrasound images have been widely exploited for more truthful pathological changes as well as diagnosis. However, they suffer from a number of shortcomings and these includes: acquisition noise from the equipment, ambient noise from the environment, the presence of background tissue, other organs and anatomical influences such as body fat, and breathing motion. Therefore, noise reduction is very important, as various types of noise generated limits the effectiveness of medical image diagnosis. In this study, an efficient analysis of MRI and ultrasound modalities is performed. Three experiments have been carried out that include various filters (Median, Gaussian and Wiener filter) and evaluating the outcomes of medical image de-noising after applying these three filters by calculating the peak signal-to-noise ratio (PSNR), which shows that Gaussian filter is better than Median and Wiene