A method for brain tumor classification from mri images using deep learning and image enhancement techniques

Magnetic resonance imaging (MRI) is a useful method for diagnosis of tumors in human brain. In this work, MRI images have been analyzed to detect the regions containing tumor and classify these regions into three different tumor categories: meningioma, glioma, and pituitary. Deep learning is a relatively recent and powerful method for image classification tasks. Therefore, faster Region-based Convolutional Neural Networks (faster R-CNN), a deep learning method, has been utilized in this study. A publicly available dataset containing 3,064 MRI brain images (708 meningioma, 1426 glioma, 930 pituitary) of 233 patients is used for training and testing of the classifier. It has been shown that faster R-CNN method can yield an accuracy of 93.14% which is higher than the related work using the same dataset. Keywords: Deep Learning, Convolutional Neural Network, Faster R-CNN, Classification, Brain Tumor