Super-Resolution Deep Learning Reconstruction for Improved Image Quality of Coronary CT Angiography-Reference-Cited by-同舟云学术

Super-Resolution Deep Learning Reconstruction for Improved Image Quality of Coronary CT Angiography

Published:2023-08-01 Issue:4 Volume:5 Page:
ISSN:2638-6135
Container-title:Radiology: Cardiothoracic Imaging
language:en
Short-container-title:Radiology: Cardiothoracic Imaging

Author:

Takafuji Masafumi¹^ORCID,Kitagawa Kakuya¹^ORCID,Mizutani Sachio¹^ORCID,Hamaguchi Akane¹,Kisou Ryosuke¹^ORCID,Iio Kotaro¹,Ichikawa Kazuhide¹,Izumi Daisuke¹^ORCID,Sakuma Hajime¹^ORCID

Affiliation:

1. From the Department of Radiology, Mie University Graduate School of Medicine, 2-174 Edobashi, Tsu 514-8507, Japan (M.T., K.K., H.S.); and Departments of Radiology (M.T., S.M., A.H., R.K.) and Cardiology (K. Iio, K. Ichikawa, D.I.), Matsusaka Municipal Hospital, Matsusaka, Japan.

Publisher

Radiological Society of North America (RSNA)

Subject

Radiology, Nuclear Medicine and imaging

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryct.230085

Reference17 articles.

1. Coronary CT Angiography and 5-Year Risk of Myocardial Infarction

2. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes

3. Diagnostic Performance of Coronary Angiography by 64-Row CT

4. Diagnostic Performance of 64-Multidetector Row Coronary Computed Tomographic Angiography for Evaluation of Coronary Artery Stenosis in Individuals Without Known Coronary Artery Disease

5. Diagnostic Accuracy of 64-Slice Computed Tomography Coronary Angiography

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