The evolution of image reconstruction for CT—from filtered back projection to artificial intelligence-Reference-Cited by-同舟云学术

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The evolution of image reconstruction for CT—from filtered back projection to artificial intelligence

Published:2018-10-30 Issue:5 Volume:29 Page:2185-2195
ISSN:0938-7994
Container-title:European Radiology
language:en
Short-container-title:Eur Radiol

Author:

Willemink Martin J.^ORCID,Noël Peter B.

Funder

German Department of Education and Research

German Research Foundation

American Heart Association

Stanford-Philips Fellowship Training Award

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging,General Medicine

Link

http://link.springer.com/content/pdf/10.1007/s00330-018-5810-7.pdf

Reference124 articles.

1. Ambrose J, Hounsfield G (1973) Computerized transverse axial tomography. Br J Radiol 46:148–149

2. Hounsfield GN (1973) Computerized transverse axial scanning (tomography). 1. Description of system. Br J Radiol 46:1016–1022

3. OECD (2017) Health at a glance 2017: OECD indicators. OECD Publishing, Paris

4. de Graaf FR, Schuijf JD, van Velzen JE et al (2010) Diagnostic accuracy of 320-row multidetector computed tomography coronary angiography in the non-invasive evaluation of significant coronary artery disease. Eur Heart J 31:1908–1915

5. Hata A, Yanagawa M, Honda O et al (2018) Effect of matrix size on the image quality of ultra-high-resolution CT of the lung: comparison of 512 x 512, 1024 x 1024, and 2048 x 2048. Acad Radiol. https://doi.org/10.1016/j.acra.2017.11.017

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