Speckle Noise Removal From Biomedical MRI Images and Classification by MSVM

Abstract

Medical images are crucial for detecting and predicting sickness, as well as for keeping track of the patient's development, owing to image processing (IP) techniques. There are numerous applications for the IP methods. Image processing is used, for instance, in the field of medicine to evaluate images produced by x-rays and MRI magnetic resonance imaging. The patient is going to incur a high price for this application. Medical images are commonly contaminated with impulsive, multiplicative, and addictive noise as a result of various image processing non-idealities. By replacing some of the original image's pixels with new ones that have luminance values that are less than the allowed dynamic luminance range, noise frequently taints medical images. In this research, the Speckle type noises are removed using the Mean Filter (MF), and the images are classified using a Multi-SVM classifier. The system was created entirely in Python.