Detection and classification of mandibular fractures in panoramic radiography using artificial intelligence.

Journal: Dento maxillo facial radiology

PMID: 38652576

Abstract

OBJECTIVES: This study evaluated the performance of the YOLOv5 deep learning model in detecting different mandibular fracture types in panoramic images.

Authors

Amir Yari

Department of Oral and Maxillofacial Surgery, School of Dentistry, Kashan University of Medical Sciences, Kashan, 8715973474, Iran.
Paniz Fasih

Department of Prosthodontics, School of Dentistry, Kashan University of Medical Sciences, Kashan, 8715973474, Iran.
Mohammad Hosseini Hooshiar

Department of Periodontics, School of Dentistry, Tehran University of Medical Sciences, Tehran, 1439955991, Iran.
Ali Goodarzi

Department of Clinical Pharmacy, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Seyedeh Farnaz Fattahi

Department of Prosthodontics, School of Dentistry, Shiraz University of Medical Sciences, Shiraz, 7195615878, Iran.

Keywords

Algorithms Artificial Intelligence Deep Learning Humans Mandibular Fractures Radiography, Panoramic Sensitivity and Specificity

External Resources

View on PubMed Access via DOI PubMed (38652576)

Detection and classification of mandibular fractures in panoramic radiography using artificial intelligence.

Abstract

Authors

Keywords

External Resources

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