Noise Reduction for Magnetic Resonance Imaging by Using Edge Detection and Hybrid Mean Lee Filter Techniques

Abstract

In this article, spatial-domain filtering algorithms were developed to suppress additive noise in magnetic resonance (MR) imaging. It is difficult to suppress MR image noise because it corrupts almost all pixels in an image. The purpose of noise reduction is to curb the noise with high efficiency while keeping the edges and other detailed features as much as possible. The present article focused on developing quite efficient noise reduction by using an edge detection technique and hybrid mean Lee filters to suppress MR image noise quite effectively in spatial domain without yielding much distortion and blurring. The performances of the developed filter were compared with the existing filters in terms of universal quality index, method noise, and execution time. Among all existing filters, the edge detection technique and hybrid mean Lee filter was found to be best for suppressing MR image noise.