Abstract #2767

Evaluation of a deep learning-based acceleration technique for ankle MRI protocol in clinical applications

Qiang Zhao¹, Jiajia Xu¹, Yu Xin Yang², Yuqing Zhao¹, Qizheng Wang¹, Yongming Dai³, and Huishu Yuan¹

¹Peking University Third Hospital, Beijing, China, ²United Imaging Research Institute of Intelligent Imaging, Beijing, China, ³Central Research Institute, United Imaging Healthcare, Shanghai, China

Synopsis

Keywords: Joints, Joints, Machine Learning/Artificial Intelligence

A deep learning-based compressed sensing (ACS) technology was recently introduced for an integrative MR acceleration solution. This study assessed the effectiveness of using ACS to evaluate ankle injuries. The ACS acceleration technique allows faster imaging than conventional acceleration methods, providing adequate image quality and diagnosis performance.

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