Design Flow for AI-driven Medical Systems Demonstrated through an Example in Dental Imaging Analysis

M. Fechner, K. Śniatała, P. Śniatała (Poznan Univ. of Techn., Poland), S. Ren (San Diego State Univ., USA), R. Śniatała, T. Pawlaczyk (Poznan Univ. of Medical Sciences, Poland)

The use of Machine Learning (ML) mechanisms for image analysis in dentistry may potentially bring many benefits. At the same time, a potential challenges may include the availability of dental images, the availability of specialist imaging equipment, and the selection of an appropriate ML model. The main goal of this paper is to propose a procedure for designing an ML-based module of a dental system for analyzing dental images, using the example of a tooth detection algorithm within images obtained from popular devices such as a camera or a smartphone. As part of this paper, a review of open access dental image datasets with assumed characteristics was conducted, followed by review of ML models used for tooth detection. Next, a proposal for the architecture of a tooth detection module was developed along with prototype version of implementation. The works carried out also constituted an extension of the DentIO system, enabling, among other things, the generation of dental diagrams based on voice commands. Further research directions may include expert verification of the presented results based on dental knowledge, as well as extension of the format of the analyzed data to include dental video analysis.