Development of a chest digital tomosynthesis R/F system and implementation of low-dose GPU-accelerated compressed sensing (CS) image reconstruction-Reference-Cited by-同舟云学术

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Development of a chest digital tomosynthesis R/F system and implementation of low-dose GPU-accelerated compressed sensing (CS) image reconstruction

Published:2018-03-23 Issue:5 Volume:45 Page:1871-1888
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Choi Sunghoon¹,Lee Haenghwa¹,Lee Donghoon²,Choi Seungyeon²,Lee Chang-Lae¹,Kwon Woocheol³,Shin Jungwook⁴,Seo Chang-Woo¹,Kim Hee-Joung¹²

Affiliation:

1. Department of Radiological Science; Yonsei University; 1 Yonseidae-gil Wonju 26493 Korea

2. Department of Radiation Convergence Engineering; Yonsei University; 1 Yonseidae-gil Wonju 26493 Korea

3. Department of Radiology; Wonju Severance Christian Hospital; 20 Ilsan-ro Wonju 26426 Korea

4. LISTEM Corporation; 94 Donghwagongdan-ro, Munmak-eup Wonju Korea

Funder

Ministry of Trade, Industry and Energy

Korea Institute for Advancement of Technology

Gangwon Institute for Regional Program Evaluation

Publisher

Wiley

Subject

General Medicine

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/mp.12843/fullpdf

Reference52 articles.

1. Cancer statistics, 2016;Siegel;CA Cancer J Clin,2016

2. The solitary pulmonary nodule on chest radiography: can we really tell if the nodule is calcified?;Berger;Am J Roentgenol,2001

3. Missed non-small cell lung cancer: radiographic findings of potentially resectable lesions evident only in retrospect 1;Shah;Radiology,2003

4. Digital x-ray tomosynthesis: current state of the art and clinical potential;Dobbins;Phys Med Biol,2003

5. Mammographic density estimation: one-to-one comparison of digital mammography and digital breast tomosynthesis using fully automated software;Tagliafico;Eur Radiol,2012

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1. Deep residual learning with Anscombe transformation for low-dose digital tomosynthesis;Journal of the Korean Physical Society;2024-06-17

2. Development of a novel algorithm to improve image quality in chest digital tomosynthesis using convolutional neural network with super-resolution;Medical Imaging 2021: Physics of Medical Imaging;2021-02-15

3. Improved digital chest tomosynthesis image quality by use of a projection-based dual-energy virtual monochromatic convolutional neural network with super resolution;PLOS ONE;2020-12-31

4. Effect of Filtered Back-Projection Filters to Low-Contrast Object Imaging in Ultra-High-Resolution (UHR) Cone-Beam Computed Tomography (CBCT);Sensors;2020-11-10

5. SART Algorithm Parallel Implementation with Siddon and MBR Methods for Digital Linear Tomosynthesis Using OpenCL;Communications in Computer and Information Science;2020

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