Benign and Malignant Tumor Classification using Machine Learning Technique
Ch. Usha Kumari1, N. Madhusudhana Rao2, M.N.V.S.S Kumar3, Kishore Pinninti4, M Pala Prasad Reddy5
1Ch. Usha Kumari, Gokaraju Rangaraju Institute of Engineering and Technology, Dept. of ECE, Hyderabad, Telangana, India.
2N.Madhusudhana Rao, Gokaraju Rangaraju Institute of Engineering and Technology, Dept. of ECE Hyderabad, Telangana, India.
3M.N.V.S.S Kumar, Aditya Institute of Technology and Management, Dept. of ECE, Tekkali, India.
4Kishore Pinninti, VNR Vignana Jyothi Institute of Engineering and Technology, Dept of ECE , Hyderabad, Telangana, India.
5M Pala Prasad Reddy, Institute of Aeronautical Engineering, Hyderabad, Telangana, India.
Manuscript received on 11 August 2019. | Revised Manuscript received on 19 August 2019. | Manuscript published on 30 September 2019. | PP: 7731-7735 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6297098319/2019©BEIESP | DOI: 10.35940/ijrte.C6297.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Brain tumor is the growth of large mass of abnormal cells in human brain. Brain tumors are of different types benign and malignant. Benign tumor is noncancerous and malignant tumor is cancerous. This research paper classifies benign and malignant using SVM classifier. The image processing techniques are used for image enhancement and restoration. Total 60 images are taken out of which 30 images are benign i.e., noncancerous images and 30 images are malignant i.e., tumor images. Image Filtration is performed on the input MRI image by using median filter. Segmentation is done using thresholding technique and Gray Level Concurrence matrix is used for the feature extraction. Features such as entropy, energy, homogeneity, correlation, contrast, IDM, RMS, standard deviation and mean are extracted for tumor region. After feature extraction all these features are given to SVM classifier to classify benign and malignant tumors. The SVM classifier has given 97.7% accuracy.
Keywords: Brain Tumor, Benign Tumor, Malignant Tumor, Feature Extraction, Classification, SVM classifier.
Scope of the Article: Classification