Learning Methods of Convolutional Neural Network Combined With Image Feature Extraction in Brain Tumor Detection

Computer-aided detection technology is less applied in brain tumor detection terminals, and it is difficult to eliminate the influence of various interference factors on the diagnosis results. In order to promote the application of computer-aided detection technology in brain tumor detection, this study based on convolutional neural network, combined with MRI detection technology to construct a model adapted to brain tumor feature detection. The main function of this research model is to segment and recognize MRI brain tumors and use convolutional layer to perform convolution operation to improve recognition efficiency and rate and combine artificially selected features with machine learning features. In addition, this article uses feature fusion to further improve the diagnostic results. Finally, this article designs experiments to perform performance analysis. The research shows that the model algorithm designed in this article has certain practical effects and can provide theoretical reference for subsequent related research.