Validation of Optimal Imaging Conditions for Coronary Computed Tomography Angiography Using High-definition Mode and Deep Learning Image Reconstruction Algorithm-Reference-Cited by-同舟云学术

Validation of Optimal Imaging Conditions for Coronary Computed Tomography Angiography Using High-definition Mode and Deep Learning Image Reconstruction Algorithm

Published:2024 Issue:5 Volume:80 Page:499-509
ISSN:0369-4305
Container-title:Japanese Journal of Radiological Technology
language:en
Short-container-title:Nippon Hoshasen Gijutsu Gakkai Zasshi

Author:

Kitera Nobuo¹,Fujioka Chikako¹,Higaki Toru²,Nishimaru Eiji¹,Yokomachi Kazushi¹,Matsumoto Yoriaki¹,Kiguchi Masao¹,Ohashi Kazuya³,Kasai Harumasa³,Awai Kazuo⁴

Affiliation:

1. Department of Radiology, Hiroshima University Hospital

2. Graduate School of Advanced Science and Engineering, Hiroshima University

3. Department of Radiology, Nagoya City University Hospital

4. Graduate School of Biomedical and Health Sciences, Hiroshima University

Publisher

Japanese Society of Radiological Technology

Link

https://www.jstage.jst.go.jp/article/jjrt/80/5/80_2024-1353/_pdf

Reference32 articles.

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5. 5） Benz DC, Fuchs TA, Gräni C, et al. Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography. Eur Heart J Cardiovasc Imaging 2018; 19(2): 193–198.