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An efficient method for brain tumor detection and categorization using MRI images by K-means clustering & DWT


Brain tumor is an uncontrolled mass of tissues in the brain which originate due to mutated growth of tissues. Brain tumor has become a leading cost of death in modern day environment and researchers are inclined to find ways to mitigate the proliferation of this disease. A lot of methods have been applied in brain tumor detection ranging from image processing to signal based analysis. In this study a robust image processing based method is applied using MRI images. MRI images are preferred due to their simplicity and low noise presence. In this study first a clustering based method is used to segment the image and then SVM is applied for tumor detection. A total seven features were considered and were analyzed by the classifiers. SVM with 94.6% accuracy gave a robust result.

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The authors of this paper express their warm regards to doctors at Rajendra institute of medical sciences for providing valuable information about this topic.

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Correspondence to Atish Chaudhary.

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Chaudhary, A., Bhattacharjee, V. An efficient method for brain tumor detection and categorization using MRI images by K-means clustering & DWT. Int. j. inf. tecnol. 12, 141–148 (2020).

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  • Tumor
  • DNA
  • Classifier
  • SVM
  • K-means
  • Cancer
  • Benign
  • Malignant