Detection and Diagnosis of Brain Tumor Using Wavelet Transform and Machine Learning Model

Abstract

Listen

Translate article

Brain tumor diagnosis using magnetic resonance images (MRI) is one of the hot topics of interest in medical field. In this paper, a novel approach for brain tumor diagnosis is proposed. Four major phases are involved in the proposed approach which are preprocessing, tumor segmentation, feature extraction and classification. Hybrid median filtering method is implemented to suppress noise. Otsu thresholding method is used for isolating tumor from its background tissues. Wavelet transform is adopted for feature extraction. Support vector machined is used for classifying the brain tumors. Classification potential of the proposed system is tested on Harvard and BRATS data set.