Research on the Application of Deep Learning in Biomedical Image Processing

Le résumé fourni par la source

With the rapid development of deep learning technology, its application in biomedical image processing has made significant progress. This article provides a comprehensive review of the application of deep learning in key biomedical fields such as medical image analysis, pathological image recognition, and cell imaging. Particular attention is paid to the application of convolutional neural networks (CNN) in image classification and segmentation, the role of recurrent neural networks (RNN) and its variants in sequence image data processing, and the application of generative adversarial networks (GAN) in high-quality biomedicine. potential in image generation. The integration and optimization of these deep learning models provides new methods and tools for accurate diagnosis, disease monitoring, and treatment. The article discusses how deep learning models can process and analyze large medical imaging datasets, and their potential applications in improving image analysis automation and accuracy.

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