Enhancing dental caries classification in CBCT images by using image processing and self-supervised learning

Diagnosing dental caries poses a significant challenge in dentistry, necessitating precise and early detection for effective management. This study utilizes Self-Supervised Learning (SSL) tasks to improve the classification of dental caries in Cone Beam Computed Tomography (CBCT) images, employing t...

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Veröffentlicht in:	Computers in biology and medicine 2024-12, Vol.183, p.109221, Article 109221
Hauptverfasser:	Zanini, Luiz Guilherme Kasputis, Rubira-Bullen, Izabel Regina Fischer, Nunes, Fátima de Lourdes dos Santos
Format:	Artikel
Sprache:	eng
Schlagworte:	CBCT Classification Computed tomography Cone-Beam Computed Tomography - methods Deep Learning Dental caries Dental Caries - classification Dental Caries - diagnostic imaging Dentistry Effectiveness Humans ICDAS Image enhancement Image processing Image Processing, Computer-Assisted - methods Medical imaging Medical research Self-supervised learning Supervised Machine Learning
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