ORIGINAL RESEARCH article
Front. Physiol.
Sec. Craniofacial Biology and Dental Research
Volume 16 - 2025 | doi: 10.3389/fphys.2025.1682917
This article is part of the Research TopicRecent Advances in Dental, Oral, and Craniofacial Bone Biology and RegenerationView all articles
Detection of Spheno-occipital Fusion Stages Using Artificial Intelligence
Provisionally accepted
- 1Necmettin Erbakan Universitesi Dis Hekimligi Fakultesi, Meram, Türkiye
- 2Ankara Universitesi, Ankara, Türkiye
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Accurate evaluation of the spheno-occipital synchondrosis (SOS) is important for growth assessment, early detection of craniofacial anomalies, and reliable forensic age estimation. This study applied three deep learning models—YOLOv5, YOLOv8, and YOLOv11—to cone-beam computed tomography (CBCT) sagittal images from 1,661 individuals aged 6 to 25 years, aiming to automate SOS fusion stage classification. Model performance was compared in terms of detection accuracy and processing speed. All models achieved high accuracy, with a mean average precision (mAP) of 0.995 in complete fusion (Stage 3). YOLOv8 demonstrated the most consistent balance of precision and recall, while YOLOv11 achieved the fastest inference time (27 ms). YOLOv5 excelled in specific stages with perfect F1-scores. These findings demonstrate that YOLO-based AI models can provide precise, rapid, and reproducible SOS assessments, offering valuable support for both clinical decision-making and forensic investigations.
Keywords: Growth and Development, Craniofacial anomaly, Spheno-occipital synchondrosis, YOLO, deep learning, artificial intelligence
Received: 09 Aug 2025; Accepted: 17 Oct 2025.
Copyright: © 2025 Uzun, Mağat and EVLİ. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: SULTAN Uzun, dtsultanuzun@gmail.com
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