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- W4382502569 abstract "Magnetic resonance imaging (MRI) is an important medical imaging method, whose major limitation is its long scan time due to the imaging mechanism, increasing patients' cost and waiting time for the examination. Currently, parallel imaging (PI) and compress sensing (CS) together with other reconstruction technologies have been proposed to accelerate image acquisition. However, the image quality of PI and CS depends on the image reconstruction algorithms, which is far from satisfying in respect to both the image quality and the reconstruction speed. In recent years, image reconstruction based on generative adversarial network (GAN) has become a research hotspot in the field of magnetic resonance imaging because of its excellent performance. In this review, we summarized the recent development of application of GAN in MRI reconstruction in both single- and multi-modality acceleration, hoping to provide a useful reference for interested researchers. In addition, we analyzed the characteristics and limitations of existing technologies and forecasted some development trends in this field.磁共振成像（MRI）是一种重要的医学成像技术，但其成像机制导致其扫描时间较长，增加了患者的检查成本与等待时间。目前已有一些技术手段，如并行成像（PI）、压缩感知（CS）等重建技术加快了其成像速度，但重建图像的质量受算法的影响。传统的重建算法在图像质量与重建速度等方面都有提高的空间。近年来，基于生成对抗网络（GAN）的方法在磁共振图像重建中展现出了优良性能，成为磁共振图像重建领域的研究热点。本文对近几年生成对抗网络在磁共振图像重建领域中的应用研究进行了全面梳理归纳，从单一模态加速重建和多模态协同加速重建两个方面综述了目前生成对抗网络在磁共振成像图像重建中的应用，以期为相关研究者提供有益参考。此外，本文还进一步分析了现有技术的特点与局限，并对未来发展趋势进行了展望。." @default.
- W4382502569 created "2023-06-30" @default.
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- W4382502569 date "2023-06-25" @default.
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- W4382502569 title "[Application of generative adversarial network in magnetic resonance image reconstruction]." @default.
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- W4382502569 doi "https://doi.org/10.7507/1001-5515.202204007" @default.
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