Keywords: Pelvis, Machine Learning/Artificial Intelligence, Deep learning reconstruction, Multi-shot DWIThis study introduced the deep learning reconstruction (DLRecon) to multi-shot DWI (MUSE-DWI) in the pelvis and aimed to investigate the changes in SNR and image quality with MUSE-DWI DLRecon. Compared with the MUSE-DWI non-DLRecon, the MUSE-DWI DLRecon showed higher SNR with stable ADC quantification. With that, DLRecon could reduce image distortion using higher shots MUSE-DWI with comparable SNR and scan time to clinically used 2-shot MUSE-DWI. This preliminary result showed the potential power of DLRecon in the pelvis allowing higher shots MUSE-DWI to be integrated in clinical practice to reduce image distortion.
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