Research on Brain Tumor Medical Image Classification Based on Deep Neural Network

This paper mainly discusses the use of deep neural networks in classifying medical images for brain tumors. Firstly, the research background is introduced, pointing out the importance of early and accurate diagnosis of brain tumors and the limitations of traditional manual analysis methods. With the development of deep neural networks, it shows great potential in the field of medical image classification. Then, the basic principles of deep neural networks are expounded. The characteristics of medical image classification are analyzed, such as the specific features of brain tumor images and the strict requirements for data quality and annotation. Then, the utilization of deep neural networks for the categorization of brain tumor images is introduced in detail: deep neural learning image classification on MATLAB taking CNN as an example. The advantages and challenges of deep neural networks in the classification of brain tumor images are discussed. Finally, the research conclusions are summarized. Deep neural networks have achieved remarkable results in the classification of medical images for brain tumors, but there are also deficiencies. The future research directions are prospected.