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Abstract #3097

Clinical Feasibility Study of Accelerated 2D Magnetic Resonance shoulder Imaging Using Deep Learning-based Algorithm

Jing Liu1, Ke Xue2, Yongming Dai2, Peng Wu2, and Jianxing Qiu1
1Peking University First Hospital, Beijing, China, 2MR Collaboration, Central Research Institute,United Imaging Healthcare, Shanghai, China

Synopsis

Deep Learning-based magnetic resonance imaging (DL-MRI) could accelerate 3D MRI scanning time. In this study, we investigate the feasibility of DL-MRI in 2D shoulder MRI. Totally 20 consecutive patients were enrolled for both conventional MRI and DL-MRI. Both qualitative and quantitative analyses were conducted to compare the image quality and lesion diagnosis on conventional MRI and DL-MRI. And our results revealed that DL-MRI was valuable for improving the overall workflow of shoulder MRI with scanning time saved and image quality improved.

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Keywords