Brain Tumour Detection of MR Image Using Naïve Beyer classifier and Support Vector Machin

Authors(2) :-R Sharmila, K Suresh Joseph

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.

Authors and Affiliations

R Sharmila
Department of Computer Science, Pondicherry University, Puducherry, India
K Suresh Joseph
Department of Computer Science, Pondicherry University, Puducherry, India

Segmentation, Histogram, K-means clustering, Naïve Bayes Classifier, Support Vector Machine (SVM)

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Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 690-695
Manuscript Number : CSEIT1833151
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

R Sharmila, K Suresh Joseph, "Brain Tumour Detection of MR Image Using Naïve Beyer classifier and Support Vector Machin", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.690-695, March-April-2018.
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