The human brain is the primary organ, and it is located in the centre of the nervous system in the human body. The abnormal cells in the brain are known as a brain tumor. The tumor in the brain does not spread to the other parts of the human body. Early diagnosis of brain tumor is required. In this work, an efficient technique is presented for magnetic resonance imaging (MRI) brain image classification using different wavelet transforms like discrete wavelet transform (DWT), stationary wavelet transform (SWT) and dual tree M-band wavelet transform (DMWT) for feature extraction and selection of coefficients and support vector machine classifier is used for classification. The normal and abnormal MRI brain image features are decomposed by DWT, SWT and DMWT. The coefficients of sub-bands are selected by rank features for the classification. Results show that DWT, SWT and DMWT produce 98% accuracy for the MRI brain classification system.

人脑是主要器官，它位于人体神经系统的中心。大脑中的异常细胞被称为脑肿瘤。脑部肿瘤不会扩散到人体其他部位。需要早期诊断脑肿瘤。在这项工作中，提出了一种有效的技术用于磁共振成像（MRI）脑图像分类，该技术使用不同的小波变换（例如离散小波变换（DWT），平稳小波变换（SWT）和双树M波段小波变换（DMWT））进行特征分类）系数的提取和选择以及支持向量机分类器用于分类。DWT，SWT和DMWT分解正常和异常的MRI脑图像特征。通过等级特征选择子带的系数以进行分类。