APA (7th ed.) Citation

JS, S., L, M., A, N., A, M., J, B., I, P., . . . CS, M. (2026). CervSpineNet: A hybrid deep learning-based approach for the segmentation of cervical spinous processes. Frontiers in bioengineering and biotechnology, 13, 1733689. https://doi.org/10.3389/fbioe.2025.1733689

Chicago Style (17th ed.) Citation

JS, Sawant, Moukheiber L, Nair A, Mahajan A, Byun J, Pichaimani I, Yoon ST, Martin CT, and Mitchell CS. "CervSpineNet: A Hybrid Deep Learning-based Approach for the Segmentation of Cervical Spinous Processes." Frontiers in Bioengineering and Biotechnology 13 (2026): 1733689. https://doi.org/10.3389/fbioe.2025.1733689.

MLA (9th ed.) Citation

JS, Sawant, et al. "CervSpineNet: A Hybrid Deep Learning-based Approach for the Segmentation of Cervical Spinous Processes." Frontiers in Bioengineering and Biotechnology, vol. 13, 2026, p. 1733689, https://doi.org/10.3389/fbioe.2025.1733689.