Image quality improvement with deep learning‐based reconstruction on abdominal ultrahigh‐resolution CT: A phantom study-Reference-Cited by-同舟云学术

Image quality improvement with deep learning‐based reconstruction on abdominal ultrahigh‐resolution CT: A phantom study

Published:2021-06-23 Issue:7 Volume:22 Page:286-296
ISSN:1526-9914
Container-title:Journal of Applied Clinical Medical Physics
language:en
Short-container-title:J Appl Clin Med Phys

Author:

Shirasaka Takashi¹,Kojima Tsukasa¹,Funama Yoshinori²,Sakai Yuki¹,Kondo Masatoshi¹,Mikayama Ryoji¹,Hamasaki Hiroshi¹,Kato Toyoyuki¹,Ushijima Yasuhiro³,Asayama Yoshiki⁴,Nishie Akihiro³

Affiliation:

1. Division of Radiology Department of Medical Technology Kyushu University Hospital Fukuoka Japan

2. Department of Medical Physics Faculty of Life Sciences Kumamoto University Kumamoto Japan

3. Department of Clinical Radiology Graduate School of Medical Sciences Kyushu University Fukuoka Japan

4. Department of Advanced Imaging and Interventional Radiology Graduate School of Medical Sciences Kyushu University Fukuoka Japan

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging,Instrumentation,Radiation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acm2.13318

Reference24 articles.

1. Influence of gantry rotation time and scan mode on image quality in ultra-high-resolution CT system

2. Ultra-High-Resolution Computed Tomography Angiography for Assessment of Coronary Artery Stenosis

3. Diagnostic performance of coronary CT angiography with ultra-high-resolution CT: Comparison with invasive coronary angiography

4. Subjective and objective comparisons of image quality between ultra-high-resolution CT and conventional area detector CT in phantoms and cadaveric human lungs

5. Effect of Matrix Size on the Image Quality of Ultra-high-resolution CT of the Lung

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