Automatisierte Erkennung und Kategorisierung von Seitenzahnrestaurationen mit Hilfe von künstlicher Intelligenz

Engels, Paula (2023): Automatisierte Erkennung und Kategorisierung von Seitenzahnrestaurationen mit Hilfe von künstlicher Intelligenz. Dissertation, LMU München: Medizinische Fakultät

Abstract

An automated detection and categorization of posterior restoration using CNN could increase the efficiency in dental practice and create a good foundation for further research. The main objective of the present dissertation project was to establish the prerequisites for the development of an AI-based algorithm for the automated detection of posterior restorations and, furthermore, to determine the diagnostic accuracy of the developed AI-algorithm in comparison to the created expert or reference standard. The image set of a total 1,761 clinical photo- graphs was divided into a training set (N=1,407) and an independent test set (N=354). The expert diagnoses served as a reference standard for cyclic train- ing and repeated evaluation of the CNN (ResNeXt-101-32x8d), which was trained by using image augmentation and transfer learning. Further statistical analysis included the calculation of contingency tables, areas under the Receiv- er Operating Characteristic Curve (AUCs) and saliency maps. After completion of the training, the CNN was able to correctly differentiate and recognize poste- rior restorations on clinical photographs with an average value of 97.1 percent. Therefore, it can be stated that the aim to develop an AI-algorithm for automatic categorization and recognition of posterior restorations was successfully com- pleted. Dental diagnostics might be supported by artificial intelligence-based algorithms in the future. To develop an applied AI-assisted evaluation system on clinical images, further research in practicability needs to be done.

• Dokumententyp: Dissertationen (Dissertation, LMU München)
• Themengebiete: 600 Technik, Medizin, angewandte Wissenschaften ; 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit
• Fakultäten: Medizinische Fakultät
• Sprache der Hochschulschrift: Deutsch
• Datum der mündlichen Prüfung: 25. Januar 2023
• 1. Bericht­erstatter:in: Kühnisch, Jan