Baştuğ, B.T.; Güneri, G.; Yıldırım, M.S.; Çorbacı, K.; Dandıl, E.
Fully Automated Detection of the Appendix Using U-Net Deep Learning Architecture in CT Scans. J. Clin. Med. 2024, 13, 5893.
https://doi.org/10.3390/jcm13195893
AMA Style
Baştuğ BT, Güneri G, Yıldırım MS, Çorbacı K, Dandıl E.
Fully Automated Detection of the Appendix Using U-Net Deep Learning Architecture in CT Scans. Journal of Clinical Medicine. 2024; 13(19):5893.
https://doi.org/10.3390/jcm13195893
Chicago/Turabian Style
Baştuğ, Betül Tiryaki, Gürkan Güneri, Mehmet Süleyman Yıldırım, Kadir Çorbacı, and Emre Dandıl.
2024. "Fully Automated Detection of the Appendix Using U-Net Deep Learning Architecture in CT Scans" Journal of Clinical Medicine 13, no. 19: 5893.
https://doi.org/10.3390/jcm13195893
APA Style
Baştuğ, B. T., Güneri, G., Yıldırım, M. S., Çorbacı, K., & Dandıl, E.
(2024). Fully Automated Detection of the Appendix Using U-Net Deep Learning Architecture in CT Scans. Journal of Clinical Medicine, 13(19), 5893.
https://doi.org/10.3390/jcm13195893