Peer-Reviewed Publication
Korean J Radiol2026;27(5):461-470.May 1, 2026Journal Article
Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study.
Seunghyun Song1, Eun-Suk Cho2, YuSik Kim3, Chulkyun Ahn4, Sang Hyun Suh1, Jae-Joon Chung1, Jong Hyo Kim5,6,7
1Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea.
2Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea. jjondol@yuhs.ac.
3Severance Institute for Vascular and Metabolic Research, Yonsei University College of Medicine, Seoul, Republic of Korea.
4ClariPi AI Medical Imaging Solutions, Seoul, Republic of Korea.
5Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, Republic of Korea.
6Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
7Advanced Institutes of Convergence Technology, Seoul National University, Seoul, Republic of Korea.
Abstract
OBJECTIVE: To evaluate the feasibility of cerebral computed tomography angiography (CTA) obtained with reduced iodine and low radiation at 70 kVp and the effect of deep learning-based augmented contrast enhancement (DL-ACE) and denoising (DL-DN) algorithms on the CTA quality.
MATERIALS AND METHODS: In this prospective study, 47 healthy volunteers (male:female, 31:16; mean age ± standard deviation…
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