Brain Tumor Detection from MRI Images using Naive Classifier
D. Divyamary, S Gopika, S. Pradeeba, M. Bhuvaneswari
Abstract
Brain tumor is the most dangerous disease and the detection of brain tumor is very essential to save one's life. The mortality rate of humans caused by the brain tumor was high before the early diagnosis of the brain tumor was identified. After the early diagnosis is found, the mortality rate is significantly decreased. Because of the exact identification of brain tumor at the starting stages, the chances of survival of a patient are increased. The classification accuracy rate is 60% more than existing ones. If the brain tumor is predicted, the position and size of the tumor can be identified and the tumor is removed from the brain. The aim of our project is to develop an efficient method to detect the brain tumor at the early stages. The various steps in the project are noise removal, morphological operation based on segmentation, feature extraction, Naive Bayes classifier initially the brain image is acquired from the patient. The acquired image is subjected to pre-processing and the feature extraction is carried out followed by classification. Therefore, we predict the brain tumor accurately by using Naive Bayes classifier method.