诊断学理论与实践2024，Vol.23Issue(2)：114-118,5.DOI:10.16150/j.1671-2870.2024.02.003
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
Application and research progress of MRI deep learning image reconstruction technology in clinical diagnosis of musculoskeletal system diseases
摘要
Abstract
Deep learning based reconstruction(DLR)technology is currently one of the most cutting-edge techno-logical advancements in the field of MRI image reconstruction.Compared to conventional MRI image reconstruction tech-niques,DLR technology redefines a new boundary between signal-to-noise ratio,spatial resolution,and scanning time on MRI.Its outstanding technical advantage is the effective removal of image noise and artifacts,significantly reducing scan-ning time,and also has potential advantages in improving the detection rate and accuracy qualitative diagnosis of lesions.With the continuous optimization of algorithms and the improvement of model generalization,DLR has been widely used in MRI examinations for multiple parts,such as the nervous system,musculoskeletal system,and heart.Its applicable scan-ning sequences and clinical application scenarios are also constantly expanding.DLR technology,while maintaining the original spatial resolution,reduces the number of signal acquisition times and increases the parallel acquisition accelera-tion factor to shorten the imaging time by more than 50%,achieving rapid imaging of the musculoskeletal system,and ob-taining significantly better image quality than traditional reconstructed images.Currently,DLR is widely used in MRI exa-minations of musculoskeletal systems,such as the knee,shoulder,wrist,and spine,and has demonstrated its outstanding performance in shortening imaging time,improving image signal-to-noise ratio and resolution.关键词
磁共振成像/深度学习图像重建/肌骨系统Key words
Magnetic resonance imaging/Deep learning-based reconstruction/Musculoskeletal system分类
医药卫生引用本文复制引用
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(2):114-118,5.基金项目
国家自然科学基金(8217189) （8217189）
