Computer aided detection and diagnosis methodology for brain stroke using adaptive neuro fuzzy inference system classifier

Abstract

AbstractA stroke or “brain attack” occurs when the blood flow to an area of the brain is interrupted. In this article, ischemic stroke is detected and diagnosed using the following stages: noise reduction, enhancement, skull removal, feature extraction and k‐means clustering. The impulse noises in brain magnetic resonance imaging (MRI) image are reduced using directional filtering algorithm. The noise reduced brain image is further enhanced using oriented local histogram equalization technique. The skull is removed from the enhanced brain image. Features are extracted and stroke region is segmented using k‐means clustering and adaptive neuro fuzzy inference system (ANFIS) classifier. The main objective of this article is to develop a methodology for the detection of stroke using MRI brain images.