Brain Tumor Segmentation and Classification using Intelligent Hybrid Morphology and Diffusion

Noise present in the images degrades the image quality as well as the performance of tumor detection from images. The main objective of this research work is to improve the image quality and develop an accurate and effective automated computer-aided diagnosis system for tumor detection from brain MR images. Contourlet transform is used for image enhancement. Thresholding and morphological operators are used for detecting tumor segment. After segmentation, features extraction and classification has been performed by using Support Vector Machine and Neural Networks. The proposed method is tested on various brain MR images and this system generates good and accurate results.