Artificial Intelligence DENTOMO: Opportunities and Prospects for analysis of CBCT in Dentistry - Aleksandr Obrubov; Evgeny Solovyh; I Arranz; F Pérez; M Tejedor; Elena Saakyan; Georgiy Kuz'michev (Elsevier, 2021)
Aim or Purpose: Analysis of artificial intelligence DENTOMO application efficiency, its opportunities and prospects for Interpretation of Cone Beam CT in Dentistry and developing model for automatic analysis cone beam computed tomography in Dentistry. Materials and Methods: The presented model is based on two convolutional neural networks, includes a database and knowledge base, harmonized with SNOMED Clinical Terms is a systematically organized computer processable collection of medical terms providing codes, terms, synonyms and definitions used in clinical documentation and reporting. The accuracy of AI model was assessed by calculating the ratio of false identifications to the true ones in each case. Results: The model of artificial intelligence DENTOMO, which allows automated deciphering the CT in maxillofacial area, was developed and implemented in practical dentistry. The developed model automatically decodes cone beam CT images, identifies, and classifies the anatomical structures of the human dental system, and reveals the pathological processes and their dynamics in dentistry system. The developed model rather accurately identified the natural teeth in the frontal group as well in the group of premolars and molars. The recognition accuracy surpassed 90%. It should be noted that the developed model includes the possibility of "training", which can improve the quality of evaluation of diagnostic features and related parameters. Moreover, it can add the current diagnostic potencies with novel features. Conclusions: Testing of DENTOMO model demonstrated a reasonable effectiveness in deciphering the CT of dental system. The developed technology allows computerizing and objectifying interpretation of CT of the dental system.