Connection

Carlo De Cecco to Coronary Vessels

This is a "connection" page, showing publications Carlo De Cecco has written about Coronary Vessels.
Connection Strength

4.134
  1. Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques. J Cardiovasc Comput Tomogr. 2019 Nov - Dec; 13(6):331-335.
    View in: PubMed
    Score: 0.512
  2. Approaches to ultra-low radiation dose coronary artery calcium scoring based on 3rd generation dual-source CT: A phantom study. Eur J Radiol. 2016 Jan; 85(1):39-47.
    View in: PubMed
    Score: 0.416
  3. Impact of an advanced image-based monoenergetic reconstruction algorithm on coronary stent visualization using third generation dual-source dual-energy CT: a phantom study. Eur Radiol. 2016 Jun; 26(6):1871-8.
    View in: PubMed
    Score: 0.412
  4. Coronary artery computed tomography scanning. Circulation. 2014 Mar 25; 129(12):1341-5.
    View in: PubMed
    Score: 0.372
  5. Dual source CT: state of the art in the depiction of coronary arteries anatomy, anatomical variants and myocardial segments. Minerva Cardioangiol. 2012 Apr; 60(2):133-46.
    View in: PubMed
    Score: 0.325
  6. Artificial Intelligence in Coronary Computed Tomography Angiography: From Anatomy to Prognosis. Biomed Res Int. 2020; 2020:6649410.
    View in: PubMed
    Score: 0.148
  7. Ischemia and outcome prediction by cardiac CT based machine learning. Int J Cardiovasc Imaging. 2020 Dec; 36(12):2429-2439.
    View in: PubMed
    Score: 0.144
  8. Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome. Am J Cardiol. 2019 11 01; 124(9):1340-1348.
    View in: PubMed
    Score: 0.135
  9. Advanced atherosclerosis imaging by CT: Radiomics, machine learning and deep learning. J Cardiovasc Comput Tomogr. 2019 Sep - Oct; 13(5):274-280.
    View in: PubMed
    Score: 0.132
  10. Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease. J Cardiovasc Comput Tomogr. 2019 May - Jun; 13(3):26-33.
    View in: PubMed
    Score: 0.131
  11. Machine learning in cardiac CT: Basic concepts and contemporary data. J Cardiovasc Comput Tomogr. 2018 May - Jun; 12(3):192-201.
    View in: PubMed
    Score: 0.124
  12. Heavily Calcified Coronary Arteries: Advanced Calcium Subtraction Improves Luminal Visualization and Diagnostic Confidence in Dual-Energy Coronary Computed Tomography Angiography. Invest Radiol. 2018 02; 53(2):103-109.
    View in: PubMed
    Score: 0.122
  13. Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve for Therapeutic Decision Making. Am J Cardiol. 2017 Dec 15; 120(12):2121-2127.
    View in: PubMed
    Score: 0.119
  14. Coronary artery assessment using self-navigated free-breathing radial whole-heart magnetic resonance angiography in patients with congenital heart disease. Eur Radiol. 2018 Mar; 28(3):1267-1275.
    View in: PubMed
    Score: 0.118
  15. Iterative beam-hardening correction with advanced modeled iterative reconstruction in low voltage CT coronary calcium scoring with tin filtration: Impact on coronary artery calcium quantification and image quality. J Cardiovasc Comput Tomogr. 2017 Sep - Oct; 11(5):354-359.
    View in: PubMed
    Score: 0.117
  16. Prognostic implications of coronary CT angiography-derived quantitative markers for the prediction of major adverse cardiac events. J Cardiovasc Comput Tomogr. 2016 Nov - Dec; 10(6):458-465.
    View in: PubMed
    Score: 0.110
  17. Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis. J Cardiovasc Comput Tomogr. 2016 Sep-Oct; 10(5):377-83.
    View in: PubMed
    Score: 0.109
  18. Dynamic CT myocardial perfusion imaging identifies early perfusion abnormalities in diabetes and hypertension: Insights from a multicenter registry. J Cardiovasc Comput Tomogr. 2016 Jul-Aug; 10(4):301-8.
    View in: PubMed
    Score: 0.108
  19. Coronary CT angiography derived morphological and functional quantitative plaque markers correlated with invasive fractional flow reserve for detecting hemodynamically significant stenosis. J Cardiovasc Comput Tomogr. 2016 May-Jun; 10(3):199-206.
    View in: PubMed
    Score: 0.107
  20. CT Evaluation of Small-Diameter Coronary Artery Stents: Effect of an Integrated Circuit Detector with Iterative Reconstruction. Radiology. 2015 Sep; 276(3):706-14.
    View in: PubMed
    Score: 0.100
  21. Discordance Between Coronary Artery Calcium Area and Density Predicts Long-Term Atherosclerotic Cardiovascular Disease Risk. JACC Cardiovasc Imaging. 2022 Nov; 15(11):1929-1940.
    View in: PubMed
    Score: 0.041
  22. Evolving Role of Calcium Density in Coronary Artery Calcium Scoring and?Atherosclerotic Cardiovascular Disease Risk. JACC Cardiovasc Imaging. 2022 09; 15(9):1648-1662.
    View in: PubMed
    Score: 0.041
  23. Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network With Long Short-term Memory for the Automated Detection of Calcified Plaques From Coronary Computed Tomography Angiography. J Thorac Imaging. 2020 May; 35 Suppl 1:S49-S57.
    View in: PubMed
    Score: 0.036
  24. Novel imaging biomarkers: epicardial adipose tissue evaluation. Br J Radiol. 2020 Sep 01; 93(1113):20190770.
    View in: PubMed
    Score: 0.035
  25. Intermodel disagreement of myocardial blood flow estimation from dynamic CT perfusion imaging. Eur J Radiol. 2019 Jan; 110:175-180.
    View in: PubMed
    Score: 0.032
  26. Dual-Energy Computed Tomography in Cardiothoracic Vascular Imaging. Radiol Clin North Am. 2018 Jul; 56(4):521-534.
    View in: PubMed
    Score: 0.031
  27. Current and future applications of CT coronary calcium assessment. Expert Rev Cardiovasc Ther. 2018 Jun; 16(6):441-453.
    View in: PubMed
    Score: 0.031
  28. Correction Factors for CT Coronary Artery Calcium Scoring Using Advanced Modeled Iterative Reconstruction Instead of Filtered Back Projection. Acad Radiol. 2016 12; 23(12):1480-1489.
    View in: PubMed
    Score: 0.028
Connection Strength

The connection strength for concepts is the sum of the scores for each matching publication.

Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.