Deep learning cone-beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects.

Palkovics D, Molnar B, Pinter C, García-Mato D, Diaz-Pinto A, Tanacs A, Dobos A, Windisch P, Ramseier CA

DOI: 10.1002/jper.70058
Published: 2026 Sep
Container: Journal of periodontology
Publisher: Not recorded
Open access: yes

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BibTeX

@article{allodium:10.1002/jper.70058,
  title = {Deep learning cone-beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects.},
  author = {Palkovics D and Molnar B and Pinter C and García-Mato D and Diaz-Pinto A and Tanacs A and Dobos A and Windisch P and Ramseier CA},
  year = {2026},
  journal = {Journal of periodontology},
  doi = {10.1002/jper.70058},
  url = {https://doi.org/10.1002/jper.70058}
}

RIS

TY  - JOUR
TI  - Deep learning cone-beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects.
AU  - Palkovics D
AU  - Molnar B
AU  - Pinter C
AU  - García-Mato D
AU  - Diaz-Pinto A
AU  - Tanacs A
AU  - Dobos A
AU  - Windisch P
AU  - Ramseier CA
PY  - 2026
JO  - Journal of periodontology
DO  - 10.1002/jper.70058
UR  - https://doi.org/10.1002/jper.70058
ER  -

APA

D, P., B, M., C, P., D, G., A, D., A, T., A, D., P, W., & CA, R. (2026). Deep learning cone-beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects.. Journal of periodontology. https://doi.org/10.1002/jper.70058

Source records

pubmed · retrieved 2026-09-25T16:19:07.503Z