Asian Journal of Engineering and Technology Innovation

Breast Tumors Ultrasound Images Classification Using Genetic Neural Algorithm

Ahmad Taha Abdulsadda

Department of communication, Al Najaf Technical College, Foundation of Technical Education, Iraq

Abstract

In this paper, we address the stability issue of 2D ARMA models for ultrasound breast images, and use the estimated 2D ARMA coefficients as feature vectors for a multi-layer perceptron neural network, which classifies the ultrasound image into: (i) normal, (ii) benign tumor, or (iii) cancerous tumor. Furthermore, we test our CAD system using genetic neural learning algorithm. Specifically, we use the estimated 2D ARMA coefficients as inputs to a genetic neural network to classify the ultrasound breast image into three regions: healthy tissue, benign tumor, and cancerous tumor. Our simulation results on various cancerous and benign ultrasound breast images illustrate the power of the proposed algorithm.

Keywords:

Tumor, ARMA model, CAD system, Genetic algorithm, Neural networks.