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Abstract #4256

Comparison between image quality of 3D T1 GRE sequence with and without deep learning reconstruction at gadoxetic acid-enhanced liver MRI

Jeong Hee Yoon1, Joonsung Lee2, Ersin Bayram3, and Jeong Min Lee1
1Radiology, Seoul National University Hospital, Seoul, Korea, Republic of, 2GE Healthcare, Seoul, Korea, Republic of, 3GE Healthcare, Houston, TX, United States


Liver magnetic resonance imaging (MRI) has been widely performed for liver lesion detection and characterization. There have been attempts to improve the image quality of T1-weighted images at liver MRI. Recently, deep learning (DL)-based reconstruction gains attention as a tool for improving the image quality without substantial computational power or difficult sequence modification.

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