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Brain tumors are the most aggressive and devastating types of cancer and are one the most common or major reason for death among individuals. The chances of survival can be increased if the cancer is detected at its early stage. This paper present an artificial neural network technique, namely feed forward back propagation neural network to classify the magnetic resonance image (MRI) into normal and timorous MRI. Image processing technique helps in detection of tumor in MRI. Feature extraction from the gray level MRI achieves using gray level co-occurence matrix (GLCM). Neural network works in two modes first is training/learning mode and second is testing/recognition mode. The whole system is developed on a MATLAB version 7.5.0 platform
Rosane Cavalcante Fragoso, Brasil
Chief Scientific Officer and Head of a Research Group
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