Brain Tumour Detection of MR Image Using Naïve Beyer classifier and Support Vector Machin
Keywords:
Segmentation, Histogram, K-means clustering, Naïve Bayes Classifier, Support Vector Machine (SVM)Abstract
Brain tumour is a mass of tissue that is structured by a gradual addition of anomalous cells and it is important to classify brain tumours from the magnetic resonance imaging (MRI) for treatment. Human investigation is the routine technique for brain MRI tumour detection and tumours classification. Interpretation of images is based on organised and explicit classification of brain MRI and various techniques have been proposed. Information identified with anatomical structures and potential abnormal tissues, which are noteworthy to treat, are given by brain tumour segmentation on MRI. A novel idea is proposed for successful identification of the brain tumor using normalized histogram and segmentation using K-means clustering algorithm. Efficient classification of the MRIs is done using Naïve Bayes Classifier and Support Vector Machine (SVM) to provide accurate prediction and classification.
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