Image denoising using Spatial Adaptive Mask Filter for medical images

In medical image processing the quality of the image is degraded in the presence of noise especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for analysis and interpretation. In this work a new technique called Spatial Adaptive Mask Filter is proposed. The proposed filter improves the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms than the mean, median, and adaptive median filters in terms of mean square error (MSE) and peak signal to noise ratio (PSNR).