Email this article Detection and classification of brain tumor using Artificial Neural Network from EEG Images
Abstract
Brain tumor is an abnormal intracranial growth caused by cells reproducing themselves in an uncontrolled manner. Curing cancer has been a major goal of medical researchers for decades. The early detection of cancer can be helpful in curing the disease completely. In this paper we propose an ANN base approach to identify brain tumor from electroencephalogram (EEG) signals. It mainly consists of three stages; they are pre-processing, feature extraction and classification. The pre-processing involves resizing so that the further processing is easier. Feature Extraction involves extracting the features. The classification stage involves Artificial Neural network. Raw EEG signals are valuable in brain tumor diagnosis. On this basis, a brain tumor identification system is developed to analyze those features to judge whether brain tumor is present or not.
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References
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