诊断学理论与实践 ›› 2024, Vol. 23 ›› Issue (02): 114-118.doi: 10.16150/j.1671-2870.2024.02.003
收稿日期:
2024-03-26
出版日期:
2024-04-25
发布日期:
2024-07-04
通讯作者:
查云飞 E-mail:zhayunfei999@126.com基金资助:
Received:
2024-03-26
Published:
2024-04-25
Online:
2024-07-04
摘要:
深度学习图像重建(deep learning-based reconstruction,DLR)技术是目前MRI图像重建领域最为前沿的技术进展之一。相对于常规MRI图像重建技术而言,DLR技术重新定义了MRI的信噪比、空间分辨率和扫描时间之间新的边界,其突出的技术优势是有效去除图像噪声及伪影,大幅缩短扫描时间,且在提高病灶的检出率和定性准确率方面也具有潜在优势。随着算法的不断优化和模型泛化性的提升,DLR目前已被广泛应用于神经系统、肌骨系统及心脏等多部位的MRI检查,其适用的扫描序列及临床应用场景也在不断拓展。DLR技术在维持原有空间分辨率条件下,通过减少信号采集次数联合增加并行采集加速因子,将成像时间缩短50%以上,实现肌骨系统快速成像,且所获得图像质量明显优于传统重建图像。目前,DLR在膝关节、肩关节、手腕关节及脊柱等肌骨系统的MRI检查中被广泛应用,并证实了其在缩短成像时间、提升图像信噪比和提高分辨率方面具有卓越表现。
中图分类号:
查云飞, 武夏夏. MRI深度学习图像重建技术在肌骨系统疾病诊断的应用进展[J]. 诊断学理论与实践, 2024, 23(02): 114-118.
ZHA Yunfei, WU Xiaxia. Application and research progress of MRI deep learning image reconstruction technology in clinical diagnosis of musculoskeletal system diseases[J]. Journal of Diagnostics Concepts & Practice, 2024, 23(02): 114-118.
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