The impact of brain tumors in medical field cannot be ignored and may lead to a short life in their highest grade. Thus, conduction of proper diagnosis that too in its early stage to improve the quality of life of patients is a necessity. Normally, several image processing techniques including computed tomography (CT) and magnetic resonance imaging (MRI) are being utilized to localize and calculate the size and tumor in a brain. But it has limited performance for accurate quantitative measurements that too in a small number of sample images. In this work, a simple yet robust classification using convolutional neural networks (CNN) for brain tumor is proposed. The investigational outcomes with low complication are anticipated and potentially compete the relevant state-of-the-art methods.
CITATION STYLE
Sinha, R., & Verma, D. (2023). Classification of Brain Tumor of Magnetic Resonance Images Using Convolutional Neural Network Approach. In Lecture Notes on Data Engineering and Communications Technologies (Vol. 142, pp. 353–361). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-3391-2_27
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