Artificial intelligence in coronary computed tomography angiography

doi:10.35711/aimi.v2.i3.73

Advanced Search

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 2, Issue 3

This Article

Academic Content and Language Evaluation of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Number of Hits and Downloads for This Article

Total Article Views (5947)

All Articles published online

The chart showing PDF series, WORD series, HTML series, Figures (1-2) series, Tables (1-2) series.

Item

Count

PDF

277

WORD

196

HTML

2900

Figures (1-2)

239

Tables (1-2)

181

Sum=3793

Featured Article

The chart showing Browse series, Download series.

Item

Count

Browse

360

Download

757

Sum=1117

Publishing Process of This Article

Item

Count

Browse

363

Download

674

Sum=1037

Jun 28, 2021 (publication date) through Apr 15, 2024

Times Cited of This Article

Times Cited (0)

Journal Information of This Article

Publication Name

Artificial Intelligence in Medical Imaging

ISSN

2644-3260

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Minireviews

Artif Intell Med Imaging. Jun 28, 2021; 2(3): 73-85
Published online Jun 28, 2021. doi: 10.35711/aimi.v2.i3.73

Full Size Figure Download Figure

Figure 2 The workflow of the fractional flow reserve-computed tomography derivation. ¹A total of 12000 coronary anatomies were generated; ²twenty-eight geometric features were extracted from the synthetically generated database; ³a deep neural network with four hidden layers was used to train the machine learning-based model. FFR-CT: Fractional flow reserve-computed tomography; CCTA: Coronary computed tomography angiography.

Citation: Zhang ZZ, Guo Y, Hou Y. Artificial intelligence in coronary computed tomography angiography. Artif Intell Med Imaging 2021; 2(3): 73-85
URL: https://www.wjgnet.com/2644-3260/full/v2/i3/73.htm
DOI: https://dx.doi.org/10.35711/aimi.v2.i3.73