Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise-Reference-Cited by-同舟云学术

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Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise

Published:2021 Issue:1 Volume:22 Page:131
ISSN:1229-6929
Container-title:Korean Journal of Radiology
language:en
Short-container-title:Korean J Radiol

Author:

Kim Joo Hee¹^ORCID,Yoon Hyun Jung¹^ORCID,Lee Eunju¹^ORCID,Kim Injoong¹^ORCID,Cha Yoon Ki²^ORCID,Bak So Hyeon³^ORCID

Affiliation:

1. Department of Radiology, Veterans Health Service Medical Center, Seoul, Korea.

2. Department of Radiology, Dongguk University Ilsan Hospital, Goyang, Korea.

3. Department of Radiology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea.

Publisher

The Korean Society of Radiology

Subject

Radiology, Nuclear Medicine and imaging

Link

https://kjronline.org/pdf/10.3348/kjr.2020.0116

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3. Clinical value of deep learning image reconstruction on the diagnosis of pulmonary nodule for ultra-low-dose chest CT imaging;Clinical Radiology;2024-08

4. Improving Image Quality and Nodule Characterization in Ultra-low-dose Lung CT with Deep Learning Image Reconstruction;Academic Radiology;2024-07

5. Low-tube-voltage whole-body CT angiography with extremely low iodine dose: a comparison between hybrid-iterative reconstruction and deep-learning image-reconstruction algorithms;Clinical Radiology;2024-06

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