Zhao Yan, Guo Qianrui, Zhang Yukun, Zheng Jia, Yang Yang, Du Xuemei, Feng Hongbo, Zhang Shuo
Department of Information Center, The First Affiliated Hospital, Dalian Medical University, Dalian 116011, China.
Department of Nuclear Medicine, Beijing Cancer Hospital, Beijing 100142, China.
Bioengineering (Basel). 2023 Sep 24;10(10):1120. doi: 10.3390/bioengineering10101120.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide. Positron emission tomography/magnetic resonance (PET/MR) imaging is a promising technique that combines the advantages of PET and MR to provide both functional and structural information of the brain. Deep learning (DL) is a subfield of machine learning (ML) and artificial intelligence (AI) that focuses on developing algorithms and models inspired by the structure and function of the human brain's neural networks. DL has been applied to various aspects of PET/MR imaging in AD, such as image segmentation, image reconstruction, diagnosis and prediction, and visualization of pathological features. In this review, we introduce the basic concepts and types of DL algorithms, such as feed forward neural networks, convolutional neural networks, recurrent neural networks, and autoencoders. We then summarize the current applications and challenges of DL in PET/MR imaging in AD, and discuss the future directions and opportunities for automated diagnosis, predictions of models, and personalized medicine. We conclude that DL has great potential to improve the quality and efficiency of PET/MR imaging in AD, and to provide new insights into the pathophysiology and treatment of this devastating disease.
阿尔茨海默病（AD）是一种进行性神经退行性疾病，影响着全球数百万人。正电子发射断层扫描/磁共振成像（PET/MR）是一种很有前景的技术，它结合了PET和MR的优势，可提供大脑的功能和结构信息。深度学习（DL）是机器学习（ML）和人工智能（AI）的一个子领域，专注于开发受人类大脑神经网络结构和功能启发的算法和模型。DL已应用于AD的PET/MR成像的各个方面，如图像分割、图像重建、诊断与预测以及病理特征可视化。在本综述中，我们介绍了DL算法的基本概念和类型，如前馈神经网络、卷积神经网络、循环神经网络和自动编码器。然后，我们总结了DL在AD的PET/MR成像中的当前应用和挑战，并讨论了自动诊断、模型预测和个性化医疗的未来方向和机遇。我们得出结论，DL在提高AD的PET/MR成像质量和效率方面具有巨大潜力，并为这种毁灭性疾病的病理生理学和治疗提供新的见解。
