Brain Hemorrhage Medical Imaging is Filtered with a PDE Based and Classified using Extracted Features

Abstract

The health and well-being industry stands as one of the most important economic sectors that mostly depend on images. The method described in the investigation's results looks for any possible bleeding. In the most recent study, we suggested a method for using computed tomography (CT) scans to detect hemorrhage in the brain. The recommended method comprises three stages: initial image processing, filtration, and feature extraction. In this study, brain hemorrhage scan images are pre-processed using a ROF filter before hemorrhage incidences are categorized. We extracted features from the head CT picture using the LDP, LPQ, LGP, and NGTDM procedures. Applying the KNN classifier after the features of the images were retrieved produced generally satisfactory results.