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Brain Tumor Classification using Multiclass Machine Learning Algorithm

Author(s):

N. Anandhi , SREE SARASWATHI THYAGARAJA COLLEGE, POLLACHI; C. Akila, SREE SARASWATHI THYAGARAJA COLLEGE, POLLACHI

Keywords:

Brain Tumor, Machine Learning Algorithm

Abstract

Most of the present predictable diagnosis techniques are based on human experience in interpreting the MRI-scan for decision; certainly this increases the possibility to false detection and identification of the brain tumor. On the other hand, applying digital image processing ensures the quick and precise detection of the tumor. classification of MR brain images is extremely important for medical analysis and interpretation. In the previous decade several methods have already been proposed. This research obtainable a novel method to classify a given MR brain image as normal or abnormal using hybrid SVM. The proposed method shared with wavelet transform and PCA. The preprocessed image is segmented using K mean algorithm. Then this images concerned wavelet conversion to extract features from images, followed by applying principle component analysis (PCA) to reduce the magnitude of features. These reduced features submitted to Hybrid Support vector machine (SVM) for classification. The proposed system used to classify the disease is in normal stage or abnormal stage such as Benign or Malignant.

Other Details

Paper ID: IJSRDV4I90478
Published in: Volume : 4, Issue : 9
Publication Date: 01/12/2016
Page(s): 890-893

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