APA (7th ed.) Citation

Qin, L., Xiao, Z., Zaki, N., Xie, Y., Qin, W., Goos, G., . . . Kim, B. (2025). Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation. Computational Mathematics Modeling in Cancer Analysis : Third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, 15181, 70-79. https://doi.org/10.1007/978-3-031-73360-4_8

Chicago Style (17th ed.) Citation

Qin, Lixue, et al. "Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation." Computational Mathematics Modeling in Cancer Analysis : Third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024, Proceedings 15181 (2025): 70-79. https://doi.org/10.1007/978-3-031-73360-4_8.

MLA (9th ed.) Citation

Qin, Lixue, et al. "Improving Single-Source Domain Generalization via Anatomy-Guided Texture Augmentation for Cervical Tumor Segmentation." Computational Mathematics Modeling in Cancer Analysis : Third International Workshop, CMMCA 2024, Marrakesh, Morocco, October 6, 2024, Proceedings, vol. 15181, 2025, pp. 70-79, https://doi.org/10.1007/978-3-031-73360-4_8.