Segmentation and Classification of Brain Tumor MRI Images Using Support Vector Machine - Mahalakshmi, G; Chellam, G. Heren (International Journal of Computer Sciences and Engineering, 2025)
This paper proposes a set of algorithms which work for the better detection and classification of Brain Tumor. The MRI image based Brain Tumor analysis would efficiently deal with classification process for Brain Tumor analysis. There are three stages namely Feature Extraction, Feature Reduction and Classification. Feature Extraction and Feature Reduction using for two algorithms. There are Discrete Wavelet Transform (DWT) and Principle Component Analysis (PCA). The Features Extracted are Mean, Standard deviation, Kurtosis, Skewness, Entropy, Contrast, Variance, Smoothness, Correlation and Energy. The result is then given to Support Vector Machine (SVM) for tumor classification as Benign or Malignant.