Brain Tumor Detection using ANNs

Nisha N. Ingole, Dhananjay E. Upasani

Abstract: Brain tumor is inherently serious and life-threatening disease. Brain tumor is an abnormal growth of cells within the brain or inside the skull, which can be cancerous or noncancerous. Early detection and classification of brain tumors is very important in clinical practice. With recent development in the medical engineering and instruments, EEG instruments are able to record the brain electric activities with high accuracy, which establishes EEG as a primary tool for diagnosing the brain abnormalities. This paper represents earlier detection of brain tumor using artificial neural networks (ANNs). EEG signals carry the information of human brain. But EEG signal is contaminated with artifacts. These artifacts are removed by adaptative filtering. Then the spectral analysis method is applied for extracting generic features in an EEG signal. Fast Fourier Transform for spectral analysis is used to separate the signal features present in noise. The clean EEG is obtained and fed to feedforward backpropagation neural network. Hence early detection of brain tumor is necessary.

Keywords: Electroencephalogram EEG, brain tumor, artifacts, adaptive filtering artificial neural network, feedforward backpropagation neural network