APA (7th ed.) Citation

D, T., TH, O., JF, H., J, S., E, T., & SB, R. (2025). Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach. Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine, 24(4), . https://doi.org/10.2463/mrms.tn.2024-0211

Chicago Style (17th ed.) Citation

D, Tamada, Oechtering TH, Heidenreich JF, Starekova J, Takai E, and Reeder SB. "Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach." Magnetic Resonance in Medical Sciences : MRMS : An Official Journal of Japan Society of Magnetic Resonance in Medicine 24, no. 4 (2025). https://doi.org/10.2463/mrms.tn.2024-0211.

MLA (9th ed.) Citation

D, Tamada, et al. "Artifact-robust Deep Learning-based Segmentation of 3D Phase-contrast MR Angiography: A Novel Data Augmentation Approach." Magnetic Resonance in Medical Sciences : MRMS : An Official Journal of Japan Society of Magnetic Resonance in Medicine, vol. 24, no. 4, 2025, https://doi.org/10.2463/mrms.tn.2024-0211.