[A deep learning segmentation model for detecting caries in molar teeth].
Zhonghua Yi Xue Za Zhi
; 102(32): 2538-2540, 2022 Aug 30.
Article
en Zh
| MEDLINE
| ID: mdl-36008325
ABSTRACT
This study aimed to build a home use deep learning segmentation model to identify the scope of caries lesions. A total of 494 caries photographs of molars and premolars collected via endoscopy were selected. Subsequently, these photographs were labeled by physicians and underwent segmentation training by using DeepLabv3+, and then verification and evaluation were performed. The mean accuracy was 0.993, the sensitivity was 0.661, the specificity was 0.997, the Dice coefficient was 0.685, and the intersection over union (IoU) was 0.529. Therefore, the present deep learning segmentation model can identify and segment the scope of caries.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Aprendizaje Profundo
Idioma:
Zh
Revista:
Zhonghua Yi Xue Za Zhi
Año:
2022
Tipo del documento:
Article
País de afiliación:
China