Filtering Magnetic Resonance Images to Detect Brain Tumor

Abstract

Magnetic resonance imaging is one of the best methods for detecting brain tumors. But the images captured by this method may contain different kinds of noises. So it is very essential to remove the noises for properly identifying the specific brain tumor. A filter is usually used to remove the noises. This paper illustrates different image filtering methods, such as low pass filter, high pass filter, and median filter, to improve the image quality by removing the noises from magnetic resonance images to identify the brain tumor. The MSE, RMSE, and the PSNR is used for understanding the quality of the filtered images. A graphical user interface is developed in MATLAB to implement all the filtering process and performance analysis for magnetic resonance images used to detect brain tumor.