SUMMARY
In this study a functional models of Artificial Neural Networks (ANNs) is proposed toaid existing diagnosis methods. ANNs are currently a “hot” research area in medicine,particularly in the fields of radiology, cardiology, and oncology. In this paper an attempt wasmade to make use of ANNs in the medical field. Hence a Computer Aided Diagnosis (CAD)system using ANNs to classify brain tumors was developed in order to detect and classify thepresence of brain tumors according to Magnetic Resonance (MR) Image, and then determinedwhich type of ANNs and activation function for ANNs is the best for image recognition. Also thestudy aimed to introduce a practical application study for brain tumor diagnosis. Neural networkmust be able to determine the state of the brain according to MR image. In all procedures, imageprocessing and ANNs design, MATLAB was incleded. From each MR Image a Harlick texturefeatures was extracted to prepare training data which was introduced to neural network as inputand target vectors. ANNs was designed using MATLAB tool "nntool". Results obtained explainElman Network, with log sigmoid activation function, surpassing other ANNs with aperformance ratio of 88.24%.