A Deep Learning Model for Idiopathic Osteosclerosis Detection on Panoramic Radiographs.
Med Princ Pract
; 31(6): 555-561, 2022.
Article
en En
| MEDLINE
| ID: mdl-36167054
ABSTRACT
OBJECTIVE:
The purpose of the study was to create an artificial intelligence (AI) system for detecting idiopathic osteosclerosis (IO) on panoramic radiographs for automatic, routine, and simple evaluations. SUBJECT ANDMETHODS:
In this study, a deep learning method was carried out with panoramic radiographs obtained from healthy patients. A total of 493 anonymized panoramic radiographs were used to develop the AI system (CranioCatch, Eskisehir, Turkey) for the detection of IOs. The panoramic radiographs were acquired from the radiology archives of the Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University. GoogLeNet Inception v2 model implemented with TensorFlow library was used for the detection of IOs. Confusion matrix was used to predict model achievements.RESULTS:
Fifty IOs were detected accurately by the AI model from the 52 test images which had 57 IOs. The sensitivity, precision, and F-measure values were 0.88, 0.83, and 0.86, respectively.CONCLUSION:
Deep learning-based AI algorithm has the potential to detect IOs accurately on panoramic radiographs. AI systems may reduce the workload of dentists in terms of diagnostic efforts.Palabras clave
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Osteosclerosis
/
Aprendizaje Profundo
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Revista:
Med Princ Pract
Asunto de la revista:
EDUCACAO
Año:
2022
Tipo del documento:
Article