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Research Status and Prospects of Deep Learning in Medical Images

机译：医学图像深度学习的研究现状与展望

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With the continuous innovation and development of artificial intelligence, the theoretical research on and application of deep learning, one of its branches, has also reached a certain height, and has become a research hotspot in all walks of life. In the medical field, traditional manual image reading and other medical image analysis methods have been unable to adapt to the sharp increase in the amount of impact data. Based on this, the combination of deep learning and medical imaging has eased this pressure. This article first briefly analyzes the relevant theories of deep learning, and focuses on its applications in medical image classification and recognition, medical image segmentation, and computer-aided diagnosis. Finally, the application of deep learning in medical images is prospected.
机译：随着人工智能的不断创新和发展，深度学习的理论研究和应用作为其分支之一，也达到了一定的高度，并已成为各行各业的研究热点。在医学领域，传统的手动图像读取和其他医学图像分析方法无法适应冲击数据量的急剧增长。基于此，深度学习和医学成像的结合缓解了这种压力。本文首先简要分析了深度学习的相关理论，并重点介绍了其在医学图像分类和识别，医学图像分割和计算机辅助诊断中的应用。最后，展望了深度学习在医学图像中的应用。

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