Cite
Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.
MLA
Bratt, Alex, et al. “Machine Learning Derived Segmentation of Phase Velocity Encoded Cardiovascular Magnetic Resonance for Fully Automated Aortic Flow Quantification.” Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance, vol. 21, no. 1, Jan. 2019, p. 1. EBSCOhost, https://doi.org/10.1186/s12968-018-0509-0.
APA
Bratt, A., Kim, J., Pollie, M., Beecy, A. N., Tehrani, N. H., Codella, N., Perez-Johnston, R., Palumbo, M. C., Alakbarli, J., Colizza, W., Drexler, I. R., Azevedo, C. F., Kim, R. J., Devereux, R. B., & Weinsaft, J. W. (2019). Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification. Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance, 21(1), 1. https://doi.org/10.1186/s12968-018-0509-0
Chicago
Bratt, Alex, Jiwon Kim, Meridith Pollie, Ashley N Beecy, Nathan H Tehrani, Noel Codella, Rocio Perez-Johnston, et al. 2019. “Machine Learning Derived Segmentation of Phase Velocity Encoded Cardiovascular Magnetic Resonance for Fully Automated Aortic Flow Quantification.” Journal of Cardiovascular Magnetic Resonance : Official Journal of the Society for Cardiovascular Magnetic Resonance 21 (1): 1. doi:10.1186/s12968-018-0509-0.