Development and verification of a convolutional neural network-based model for automatic mandibular canal localization on multicenter CBCT images
Abstract Objectives Development and verification of a convolutional neural network (CNN)-based deep learning (DL) model for mandibular canal (MC) localization on multicenter cone beam computed tomography (CBCT) images. Methods In this study, a total 1056 CBCT scans in multiple centers were collected...
Saved in:
| Main Authors: | Xiao Pan, Chengtao Wang, Xuhui Luo, Qi Dong, Haiyang Sun, Wentao Zhang, Hongyan Qu, Runzhi Deng, Zitong Lin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
BMC
2025-08-01
|
| Series: | BMC Oral Health |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12903-025-06724-6 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
AI-powered segmentation of bifid mandibular canals using CBCT
by: Ismail Gumussoy, et al.
Published: (2025-06-01) -
Evaluation of the cortication ratio and visibility of mandibular canal and mandibular incisive canal in patients with mandibular cortical index type 1 on cone-beam computed tomography images
by: Roghieh Bardal, et al.
Published: (2024-07-01) -
Prevalence and morphology of middle mesial canals in mandibular first molars and their relationship with anatomical aspects of the mesial root: a CBCT analysis
by: Dandan Wang, et al.
Published: (2025-01-01) -
Radiographic and anatomic investigation on the prevalence of bifid mandibular canals in cone beam computed tomography scans
by: C. Casagrande, et al.
Published: (2018-09-01) -
Location of the mandibular incisal canal regarding to the root apices: a cone-beam computed tomography study
by: Z. S. Khabadze, et al.
Published: (2020-03-01)