1.YOLOv8m-segmentation for detecting cervical burnout and caries in bitewing radiographs:A deep learning approach
Mohd Isyrafuddin Bin ISMAIL ; Nooritawati Md TAHIR ; Wan Syahirah Binti W. SAMSUDIN ; Mas Suryalis AHMAD ; Nashuha OMAR ; Mohd Yusmiaidil Putera Mohd YUSOF
Imaging Science in Dentistry 2026;56(1):26-35
Purpose:
This study evaluated the performance of the YOLOv8m-seg model in detecting and delineating interproximal caries and cervical burnout on bitewing radiographs and examined whether increasing the number of training epochs improved segmentation accuracy and consistency.
Materials and Methods:
In total, 1,410 bitewing radiographs were annotated using polygon-based masks by a trained dental clinician. The YOLOv8m-seg model was trained for 50, 100, and 150 epochs on 1,128 images and validated on 282 images using the Ultralytics segmentation framework. Model performance was assessed using precision, recall, and mean average precision at intersection-over-union thresholds of 0.5 and 0.5 to 0.95 (mAP0.5, mAP0.5-0.95) for both bounding box and mask outputs. Additional evaluation was conducted on a non-augmented validation subset.
Results:
Extended training duration was associated with improved segmentation performance. The highest mask mAP0.5-0.95 value was 0.828 at epoch 150. Both box-based precision and recall increased with longer training, whereas mask-based evaluation more accurately reflected the model’s ability to delineate the boundaries of caries and cervical burnout. Performance appeared consistent across both classes in the augmented validation split but was reduced in the non-augmented validation subset.
Conclusion
The YOLOv8m-seg model demonstrated high diagnostic accuracy in distinguishing proximal caries from cervical burnout on bitewing radiographs. Its mask-based outputs may assist clinicians in early lesion recognition and support improved diagnostic decision-making. Future studies should evaluate model generalizability across broader populations and diverse clinical environments and should prioritize assessment using non-augmented validation sets and independent test datasets.
2.A MULTIDISCIPLINARY APPROACH TO MANAGING BIMAXILLARY HYPERHYPODONTIA: A CASE REPORT
Mohd Isyrafuddin Bin Ismail ; Siti Hajar Hamzah ; Alaa Sabah Hussein ; Syed Bazli Alwi Syed Bakhtiar Ariffin ; Mohd Kherman Suparman ; Ilham Wan Mokhtar ; Mas Suryalis Ahmad
Journal of University of Malaya Medical Centre 2023;26(1):179-184
Bimaxillary hyperhypodontia (BHH) is a very rare numeric anomaly with a prevalence of 0.002% to 3.1% described by the presence of a supernumerary tooth in the premaxilla region and a missing mandibular incisor tooth. This case highlights the multidisciplinary management of a child presenting with BHH who complies with the recommended protocol by surgically removing the supernumerary tooth and then proceeding with orthodontic treatment for function and aesthetics. A 9-year-old healthy Malay boy presented with a fully erupted tooth 21, a labially palpable bulge of unerupted tooth 11, a missing tooth 32, and a tendency for an anterior and posterior crossbite. The radiographs showed an inverted, unerupted, conical-shaped supernumerary tooth overlapping the unerupted tooth 11 and hypodontia of tooth 32. The management was surgical removal of the supernumerary tooth and the placement of an upper removable appliance with a palatal expansion screw followed by comprehensive fixed orthodontics.
Case Reports [Publication Type]


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