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• Special Focus •
Editorial comment: the progress in clinical application of deep learning MRI reconstruction algorithm
YAN Fuhua 

Cite this article as: YAN F H. Editorial comment: the progress in clinical application of deep learning MRI reconstruction algorithm[J]. Chin J Magn Reson Imaging, 2024, 15(10): 1-2. DOI:10.12015/issn.1674-8034.2024.10.001.


[Abstract] Deep learning reconstruction (DLR) algorithm is gradually mature and has become the most cutting-edge technology in the field of MRI. With the continuous optimization of DLR algorithms and the improvement of model generalization, the scope of application is becoming wider and wider, which plays an important role in optimizing clinical process, improving image quality and disease diagnosis. DLR algorithm can effectively reduce image noise, reduce or even eliminate motion artifacts, shorten scanning time, provide higher contrast, and optimize diagnostic efficiency. With the continuous development and maturity of various DLR algorithms, the scope of clinical application is also expanding, expanding from the previous 2D sequence to 3D sequence, from structural imaging to functional imaging, and gradually showing its potential advantages, which will definitely help improve the ability of MRI disease diagnosis. This paper summarized the clinical application of MRI DLR algorithm to provide reference for related research.
[Keywords] magnetic resonance imaging；deep learning；image reconstruction；algorithm

YAN Fuhua1, 2*  

1 Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China

2 Faculty of Medical Imaging Technology, College of Health Science and Technology, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China

Corresponding author: YAN F H, E-mail: yfh11655@rjh.com.cn

Conflicts of interest   None.

Received  2024-09-19
Accepted  2024-10-08
DOI: 10.12015/issn.1674-8034.2024.10.001
Cite this article as: YAN F H. Editorial comment: the progress in clinical application of deep learning MRI reconstruction algorithm[J]. Chin J Magn Reson Imaging, 2024, 15(10): 1-2. DOI:10.12015/issn.1674-8034.2024.10.001.

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