Deep learning-based image reconstruction for few-view computed tomography-Reference-Cited by-同舟云学术

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Deep learning-based image reconstruction for few-view computed tomography

Published:2021-09 Issue: Volume:1011 Page:165594
ISSN:0168-9002
Container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
language:en
Short-container-title:Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment

Author:

Yim Dobin,Lee Seungwan,Nam Kibok,Lee Dahye^ORCID,Kim Do Kyung,Kim Jong-Seok^ORCID

Funder

National Research Foundation of Korea

Ministry of Science, ICT and Future Planning

Publisher

Elsevier BV

Subject

Instrumentation,Nuclear and High Energy Physics

Reference26 articles.

1. Emerging clinical applications of computed tomography;Liguori;Med. Devices,2015

2. Principles of Computerized Tomographic Imaging;Kak,1988

3. Computed Tomography: Principles, Design, Artifacts, and Recent Advances;Hsieh,2015

4. Tomographic image reconstruction using filtered back projection (FBP) and algebraic reconstruction technique (ART);Chetih,2015

5. Simultaneous algebraic reconstruction technique (SART): A superior implementation of the ART algorithm;Andersen;Ultrason. Imaging,1984

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3. Low-contrast assessment on deep learning-based reconstruction of CT images;AIP Conference Proceedings;2024

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