APA (7th ed.) Citation

Konietzke, M., Triphan, S. M. F., Eichinger, M., Bossert, S., Heller, H., Wege, S., . . . Wielpütz, M. O. (2022). Unsupervised clustering algorithms improve the reproducibility of dynamic contrast-enhanced magnetic resonance imaging pulmonary perfusion quantification in muco-obstructive lung diseases. Frontiers in medicine, 9, . https://doi.org/10.3389/fmed.2022.1022981

Chicago Style (17th ed.) Citation

Konietzke, Marilisa, et al. "Unsupervised Clustering Algorithms Improve the Reproducibility of Dynamic Contrast-enhanced Magnetic Resonance Imaging Pulmonary Perfusion Quantification in Muco-obstructive Lung Diseases." Frontiers in Medicine 9 (2022). https://doi.org/10.3389/fmed.2022.1022981.

MLA (9th ed.) Citation

Konietzke, Marilisa, et al. "Unsupervised Clustering Algorithms Improve the Reproducibility of Dynamic Contrast-enhanced Magnetic Resonance Imaging Pulmonary Perfusion Quantification in Muco-obstructive Lung Diseases." Frontiers in Medicine, vol. 9, 2022, https://doi.org/10.3389/fmed.2022.1022981.