医学影像跨模态生成方法综述

Review of Medical Imaging Cross-Modal Generation Methods

  • 摘要: 摘要:在当今快速发展的医学人工智能领域,基于深度学习的图像生成算法已成为研究的热点之一。本文旨在综述自回归模型、变分自编码器、生成式对抗网络和扩散模型这四种主流图像生成算法的发展现状,并从计算机断层扫描、磁共振成像和计算机断层血管造影三种模态分析生成式模型在医学多模态影像转换中的应用。生成模型在医学影像领域不仅具有广阔的应用前景,还有巨大的价值潜力。

     

    Abstract: Abstract: In the rapidly developing field of medical artificial intelligence, image generation algorithm based on deep learning has become one of the research hotspots. This paper aims to review the development status of four major image generation algorithms, namely autoregressive model, variational autoencoder, generative adversarial network and diffusion model, and analyze the application of generative model in medical multimodal image conversion from three modes: computed tomography, magnetic resonance imaging and computed tomography angiography.Generative model not only has broad application prospects in the field of medical imaging, but also has great value potential.

     

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