Design a classification system for brain magnetic resonance image

Abstract EN

Automated and accurate classification of brain MRI is such important that leads us to present a new robust classification technique for analyzing magnetic resonance images [Chris 2003].

In this work, the proposed method consist of three stages collection of images, feature extraction, and classification.

We are used gray-level co-occurrence matrix (GLCM) is used to extract features from brain MRI.

These features are given as input to k-nearest neighbor (K-NN) classifier to classify images as normal or abnormal brain MRI.