A customised 3D U-Net model for bifid mandibular canal segmentation and detection on CBCT: a diagnostic accuracy study.

Aboseif S, Anter E, Khairy E

DOI: 10.1186/s12903-026-08336-0
Published: 2026 Apr 23
Container: BMC oral health
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s12903-026-08336-0,
  title = {A customised 3D U-Net model for bifid mandibular canal segmentation and detection on CBCT: a diagnostic accuracy study.},
  author = {Aboseif S and Anter E and Khairy E},
  year = {2026},
  journal = {BMC oral health},
  doi = {10.1186/s12903-026-08336-0},
  url = {https://doi.org/10.1186/s12903-026-08336-0}
}

RIS

TY  - JOUR
TI  - A customised 3D U-Net model for bifid mandibular canal segmentation and detection on CBCT: a diagnostic accuracy study.
AU  - Aboseif S
AU  - Anter E
AU  - Khairy E
PY  - 2026
JO  - BMC oral health
DO  - 10.1186/s12903-026-08336-0
UR  - https://doi.org/10.1186/s12903-026-08336-0
ER  -

APA

S, A., E, A., & E, K. (2026). A customised 3D U-Net model for bifid mandibular canal segmentation and detection on CBCT: a diagnostic accuracy study.. BMC oral health. https://doi.org/10.1186/s12903-026-08336-0

Source records

pubmed · retrieved 2026-09-26T12:09:09.492Z