APA (7th ed.) Citation

PP, A., S, K., AP, J., C, M., & SA, C. (2026). Development and Validation of a Deep Learning-Based Segmentation Method for Fenestration Marker and Graft Body Identification in Fenestrated Endovascular Aortic Repair. Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists, 15266028261437610. https://doi.org/10.1177/15266028261437610

Chicago Style (17th ed.) Citation

PP, Akouris, Kim S, Javidan AP, McIntosh C, and Crawford SA. "Development and Validation of a Deep Learning-Based Segmentation Method for Fenestration Marker and Graft Body Identification in Fenestrated Endovascular Aortic Repair." Journal of Endovascular Therapy : An Official Journal of the International Society of Endovascular Specialists 2026: 15266028261437610. https://doi.org/10.1177/15266028261437610.

MLA (9th ed.) Citation

PP, Akouris, et al. "Development and Validation of a Deep Learning-Based Segmentation Method for Fenestration Marker and Graft Body Identification in Fenestrated Endovascular Aortic Repair." Journal of Endovascular Therapy : An Official Journal of the International Society of Endovascular Specialists, 2026, p. 15266028261437610, https://doi.org/10.1177/15266028261437610.