Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT-Reference-Cited by-同舟云学术

Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT

Published:2022 Issue:7 Volume:23 Page:752
ISSN:1229-6929
Container-title:Korean Journal of Radiology
language:en
Short-container-title:Korean J Radiol

Author:

Son Wookon¹^ORCID,Kim MinWoo²^ORCID,Hwang Jae-Yeon¹³^ORCID,Kim Yong-Woo¹^ORCID,Park Chankue¹^ORCID,Choo Ki Seok¹^ORCID,Kim Tae Un¹^ORCID,Jang Joo Yeon¹^ORCID

Affiliation:

1. Department of Radiology, Pusan National University Yangsan Hospital, Yangsan, Korea.

2. School of Biomedical Convergence Engineering, Pusan National University, Busan, Korea.

3. Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, College of Medicine, Pusan National University, Yangsan, Korea.

Publisher

The Korean Society of Radiology

Subject

Radiology, Nuclear Medicine and imaging

Link

https://kjronline.org/pdf/10.3348/kjr.2021.0466

Reference25 articles.

1. Radiation Risk to Children From Computed Tomography

2. Methods for Clinical Evaluation of Noise Reduction Techniques in Abdominopelvic CT

3. State of the Art: Iterative CT Reconstruction Techniques

4. Abdominal CT: Comparison of Adaptive Statistical Iterative and Filtered Back Projection Reconstruction Techniques

5. Model-based Iterative Reconstruction: Effect on Patient Radiation Dose and Image Quality in Pediatric Body CT

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