IRJET - An Efficient Approach for Multi-Modal Brain Tumor Classification using Texture Features and Machine Learning

This paper proposes an efficient approach for multi-modal brain tumor classification using texture features and machine learning. It uses the MICCAI BraTS 2016 dataset and segments tumors using fuzzy c-means clustering. It then extracts texture features like GLCM and LBP and classifies tumors as benign or malignant using an SVM classifier. The proposed method achieved accurate segmentation and classification of brain tumors in MRI images.