Brain tumor detection using anfis classifier and segmentation

The human brain is the most interesting and intricate mechanism in the human body which is comprised of hundreds of billions of neurons and that has prompted a considerable lot of research of the organ. Some of the primary activities of the human brain are to govern muscles, and coordinate bodily movement, sensory perceptions, memory, learning, speech, emotions, intelligences and consciousness. The abnormal proliferation of cells in brain leads to the establishment of the tumor in brain. In this study effort, an automated brain tumor detection and segmentation technology is suggested. The suggested technique comprises of feature extraction, classification and segmentation. In this study, Gray Level Co-occurrence Matrix (GLCM) based features, Discrete Wavelet Transform (DWT) co-efficient and Laws texture features are employed. These characteristics are learned and categorised into either normal or pathological using Adaptive Neuro Fuzzy Inference System (ANFIS) classifier. Morphological procedures are conducted on the categorized abnormal brain imaging in order to separate the tumor areas.