Denoising of Magnetic Resonance Images Using Wavelet Transform

Abstract

Magnetic Resonance Imaging (MRI) is a non-invasive medical imaging technique that creates detailed images of the body's organs, tissues, and physiological processes. MR images are often influenced by various noise types during acquisition and transmission, which can lead to detection and diagnostic difficulties and errors. Wavelets are mathematical tools for separating data into time-frequency components and analyzing them. Experiments show that the discrete wavelet transform families, including the Haar, Daubechies, and Symlets functions, can improve the quality of noisy images. Daubechies family is found to achieve the best results relative to the other families in terms of removing noise and preserving the details of the image.