A survey on artificial intelligence approaches for medical image classification

In this paper, a survey has been made on the applications of intelligent computing techniques for diagnostic sciences in biomedical image classification. Several state-of-the-art Artificial Intelligence (AI) techniques for automation of biomedical image classification are investigated. This study gathers representative works that exhibit how AI is applied to the solution of very different problems related to different diagnostic science analysis. It also detects the methods of artificial intelligence that are used frequently together to solve the special problems of medicine. SVM neural network is used in almost all imaging modalities of medical image classification. Similarly fuzzy C means and improvements to it are important tool in segmentation of brain images. Various diagnostic studies like mammogram analysis, MRI brain analysis, bone and retinal analysis etc., using neural network approach result in use of back propagation network, probabilistic neural network, and extreme learning machine recurrently. Hybrid approach of GA and PSO are also commonly used for feature extraction and feature selection. Keywords: Medical Imaging, Artificial Intelligence (AI), Neural Networks (NN), Fuzzy Logic (FL), Genetic Algorithms (GA), Particle Swarm Optimization (PSO)