KJR Honors Most Impactful Article and Distinguished Reviewers for 2023
Author:
Affiliation:
1. Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Publisher
XMLink
Subject
Radiology, Nuclear Medicine and imaging
Link
https://kjronline.org/pdf/10.3348/kjr.2023.0810
Reference7 articles.
1. KJR Ways to Recognize Most Impactful Articles and Distinguished Reviewers
2. Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise
3. Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction
4. Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT
5. Image Quality and Lesion Detectability of Lower-Dose Abdominopelvic CT Obtained Using Deep Learning Image Reconstruction
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