BRAIN TUMOR CLASSIFICATION USING ARTIFICIAL NEURAL NETWORK ON MRI IMAGES

Shubhangi S. Veer (Handore), Pradeep M. Patil

Abstract: In this paper, an attempt has been made to summarize the multi-resolution transformation and the different classifiers useful to analyze the brain tumor using MRI. X-ray, MRI, Ultrasound etc. are different techniques used to scan brain tumor images. Radiologist prefers MRI to get detail information about tumor to help him diagnoses. In this paper we have used MRI of brain tumor for analysis. We have used Digital image processing tool for detection of the tumor. The identification, detection and classification of brain tumor have been done by extracting features from MRI with the help of wavelet transformation. The MRI of brain tumor is classified into two categories normal and abnormal brain. In this work Digital image processing has been used as a tool for getting clear and exact details about tumor in earlier stages. This helps the physicians and practitioners for diagnoses

Keywords: Brain tumor, Wavelet transform, segmentation

DOI: https://doi.org/10.15623/ijret.2015.0412042