K.V. Kulhalli and S.R.Khot, D.Y.Patil College of Engineering and Technology, India

The Main purpose of this paper is to design, implement and evaluate a strong automatic diagnostic system that increases the accuracy of tumor diagnosis in brain using MR images. This presented work classifies the brain tissues as normal or abnormal automatically, using computer vision. This saves lot of radiologist time to carryout monotonous repeated job. The acquired MR images are processed using image preprocessing techniques. The preprocessed images are then segmented, and the various features are extracted. The extracted features are fed to the artificial neural network as input that trains the network using error back propagation algorithm for correct decision making.

Magnetic Resonance Imaging, Computer Tomography, Artificial Neural Network , Histogram Equalization , Brain Abnormality .