Brain tumor is one in all the extraordinary illness causes death among the people. Neoplasm is associate unconfined expansion of tissue in any neighborhood of the body. During the process have a tendency to tend to stand live taking man photos as input; resonance imaging that is guided into internal cavity of brain and offers the entire image of brain. In this paper brain tumor detection system is proposed. Here bunch methodology supported intensity was enforced. The Probabilistic Neural Network square measure used to identify the various levels of tumor like Malignant, Benign or traditional. PNN with Radial Basis are used for classification and segmentation of cells. In order to classify the normal or abnormal cells, proper decision need to be taken. This could be done in 2 levels: Gray-Level Co-occurrence Matrix and the classification are performed based on Neural Networks. The tumor cell detection is manually performed by the schematic methodology for X-radiation.
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