Research on magetic resonance image denoising for medical applications

• Main Author: Ma, Yu Ze
• Other Authors: Mohammed Yakoob Siyal
• Format: Final Year Project
• Language: English
• Published: 2018
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/76273
• Institution: Nanyang Technological University

This project mainly studies the magnetic resonance imaging (MRI) de-noising problem. In modern medicine, magnetic resonance imaging has become an important auxiliary tool for doctor to diagnosis and treatment of disease. There is a very important role of the de-noising research in medicine. Most existing de-noising method assumes that the noise variance is known, get rid of noise from the image directly. Image processing is a very basic and direct image processing method in the image enhancement processing technology. It is also an important part of the image digital software and the image display software. Gray-scale transformation is a method of changing the gray value of each pixel in an original image according to certain target conditions according to certain transformation relations. The purpose is to improve the image quality and make the image display more clear. Image de-noising is an important step in digital image processing. The effect of de-noising directly affects subsequent image processing, such as image segmentation, edge detection and so on. The image signal may be polluted by noise during the process of generation and transmission. The common noise in general digital image system mainly includes Gauss noise (mainly produced by the interior of resistive components), salt and pepper noise (mainly the white spot noise on the black image caused by the image cutting or the Poisson noise produced in the process of photoelectric conversion).