Brain tumor classification model of ResNet-50 network based on different data enhancement algorithms
Menghan Zou, Mingze Ma, Anan Wang, Yujie Li, Teoh Teik Toe · 2023
The accuracy and stability of brain tumor MRI image classification is significant for the healthcare system, but the traditional models have the defects of difficulty in handling complex features and unstable classification. In this paper, we propose a novel brain tumor classification model based on residual neural network, and use three different data enhancement algorithms: geometric transformation, mixup, and SamplePairing to process a dataset containing four different types of brain tumor images, and finally evaluate the classification effect of our proposed model. Among them, the best results were achieved by using geometric transformations for data enhancement.