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Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023
Yong Jun Jung1, Sang Hyun Choi1, Subin Heo1
1Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 88 Olympic-Ro 43-Gil, Songpa-Gu, Seoul 05505, Republic of Korea.
Interreader agreement for Liver Imaging Reporting and Data System (LI-RADS) ancillary features (AFs) in CT/MRI v2018 varied. Features favoring malignancy showed higher agreement than those favoring benignity, guiding clinical application.
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