Deep Learning Towards Brain Tumor Detection Using MRI Images

Abstract

Brain is a significant part that plays a vital role in the human body. Brain tumor is the abnormal growth of the cell in the brain. Early detection is required to locate the tumor as well as to know the tumor’s maturity level; otherwise, it is so dangerous that it becomes an executioner of human beings. Unlike other radiographic images, Magnetic Resonance Imaging (MRI) plays an important role in detection of brain tumor. Other than any clinical approaches, many researchers have used computer aided technologies, which suffer from either insufficient accuracy or longer execution time. Moreover, correct classification of brain tumor is important to detect the types of tumor. In this paper, a deep learning model has been developed by using enhanced techniques for observing visual substances (unnatural growth) in an MRI image. In the proposed approach, CNN wavelet transformation is used for feature extraction and Capsule network is used for classification purpose. The experimental results prove that the proposed technique has achieved better accuracy and produced the result with reduced execution time.