Journal of Cardiovascular Computed Tomography, 1934-5925

Journal

  1. 2020
  2. Abadia, A. F., van Assen, M., Martin, S. S., Vingiani, V., Griffith, L. P., Giovagnoli, D. A., Bauer, M. J., & Schoepf, U. J. (2020). Myocardial extracellular volume fraction to differentiate healthy from cardiomyopathic myocardium using dual-source dual-energy CT. Journal of Cardiovascular Computed Tomography, 14(2), 162-167. https://doi.org/10.1016/j.jcct.2019.09.008
  3. 2019
  4. Mastrodicasa, D., Albrecht, M. H., Schoepf, U. J., Varga-Szemes, A., Jacobs, B. E., Gassenmaier, S., De Santis, D., Eid, M. H., van Assen, M., Tesche, C., Mantini, C., & De Cecco, C. N. (2019). Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFRML): Impact of iterative and filtered back projection reconstruction techniques. Journal of Cardiovascular Computed Tomography, 13(6), 331-335. https://doi.org/10.1016/j.jcct.2018.10.026
  5. van Assen, M., De Cecco, C. N., Sahbaee, P., Eid, M. H., Griffith, L. P., Bauer, M. J., Savage, R. H., Varga-Szemes, A., Oudkerk, M., Vliegenthart, R., & Schoepf, U. J. (2019). Feasibility of extracellular volume quantification using dual-energy CT. Journal of Cardiovascular Computed Tomography, 13(1), 81-84. https://doi.org/10.1016/j.jcct.2018.10.011
  6. van Assen, M., De Cecco, C. N., Eid, M., von Knebel Doeberitz, P., Scarabello, M., Lavra, F., Bauer, M. J., Mastrodicasa, D., Duguay, T. M., Zaki, B., Lo, G. G., Choe, Y. H., Wang, Y., Sahbaee, P., Tesche, C., Oudkerk, M., Vliegenthart, R., & Schoepf, U. J. (2019). Prognostic value of CT myocardial perfusion imaging and CT-derived fractional flow reserve for major adverse cardiac events in patients with coronary artery disease. Journal of Cardiovascular Computed Tomography, 13(3), 26-33. https://doi.org/10.1016/j.jcct.2019.02.005
  7. 2018
  8. Singh, G., Al'Aref, S. J., Van Assen, M., Kim, T. S., van Rosendael, A., Kolli, K. K., Dwivedi, A., Maliakal, G., Pandey, M., Wang, J., Do, V., Gummalla, M., De Cecco, C. N., & Min, J. K. (2018). Machine learning in cardiac CT: Basic concepts and contemporary data. Journal of Cardiovascular Computed Tomography, 12(3), 192-201. https://doi.org/10.1016/j.jcct.2018.04.010
  9. 2017
  10. 2016
  11. Tesche, C., De Cecco, C. N., Vliegenthart, R., Duguay, T. M., Stubenrauch, A. C., Rosenberg, R. D., Varga-Szemes, A., Bayer, R. R., Yang, J., Ebersberger, U., Baguet, M., Jochheim, D., Hoffmann, E., Steinberg, D. H., Chiaramida, S. A., & Schoepf, U. J. (2016). Coronary CT angiography-derived quantitative markers for predicting in-stent restenosis. Journal of Cardiovascular Computed Tomography, 10(5), 377-383. https://doi.org/10.1016/j.jcct.2016.07.005
  12. 2015

ID: 19494170