Hybrid gray wolf optimizer-artificial neural network classification approach for magnetic resonance brain images.
Journal:
Applied optics
Published Date:
Mar 1, 2018
Abstract
Automated and accurate classification of magnetic resonance images (MRIs) of the brain has great importance for medical analysis and interpretation. This paper presents a hybrid optimized classification method to classify the brain tumor by classifying the given magnetic resonance brain image as normal or abnormal. The proposed system implements a gray wolf optimizer (GWO) combined with a supervised artificial neural network (ANN) classifier to achieve enhanced MRI classification accuracy via selecting the optimal parameters of ANN. The introduced GWO-ANN classification system performance is compared to the traditional neural network (NN) classifier using receiver operating characteristic analysis. Experimental results obviously indicate that the presented system achieves a high classification rate and performs much better than the traditional NN classifier.