Ability of artificial intelligence to diagnose coronary artery stenosis using hybrid images of coronary computed tomography angiography and myocardial perfusion SPECT-Reference-Cited by-同舟云学术

Ability of artificial intelligence to diagnose coronary artery stenosis using hybrid images of coronary computed tomography angiography and myocardial perfusion SPECT

Published:2019-03-18 Issue:1 Volume:3 Page:
ISSN:2510-3636
Container-title:European Journal of Hybrid Imaging
language:en
Short-container-title:European J Hybrid Imaging

Author:

Yoneyama Hiroto^ORCID,Nakajima Kenichi,Taki Junichi,Wakabayashi Hiroshi,Matsuo Shinro,Konishi Takahiro,Okuda Koichi,Shibutani Takayuki,Onoguchi Masahisa,Kinuya Seigo

Publisher

Springer Science and Business Media LLC

Subject

Radiology Nuclear Medicine and imaging,Molecular Medicine,Biophysics,Computer Science (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1186/s41824-019-0052-8.pdf

Reference29 articles.

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2. Arsanjani R, Xu Y, Dey D, Fish M, Dorbala S, Hayes S et al (2013a) Improved accuracy of myocardial perfusion SPECT for the detection of coronary artery disease using a support vector machine algorithm. J Nucl Med 54:549–555

3. Arsanjani R, Xu Y, Dey D, Vahistha V, Shalev A, Nakanishi R et al (2013b) Improved accuracy of myocardial perfusion SPECT for detection of coronary artery disease by machine learning in a large population. J Nucl Cardiol 20:553–562

4. Danad I, Raijmakers PG, Driessen RS, Leipsic J, Raju R, Naoum C et al (2017) Comparison of coronary CT angiography, SPECT, PET, and hybrid imaging for diagnosis of ischemic heart disease determined by fractional flow reserve. JAMA Cardiol 10:1100–1107

5. Guner LA, Karabacak NI, Akdemir OU, Karagoz PS, Kocaman SA, Cengel A et al (2010) An open-source framework of neural networks for diagnosis of coronary artery disease from myocardial perfusion SPECT. J Nucl Cardiol 17:405–413

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