Advancements in the Detection of Dental Filling using the ResNet Neural Network

Numerous individuals face issues with their dental health, and to obtain the treatment they require, dental professionals. The continuous lack of dentists, despite breakthroughs in dental methods, have led to the invention of instruments to help dentists treat patients more effectively. Enhancing the precision of tooth fillings, a required dental operation is the aim of the present study. Many ResNet variants are used with the Mask Region-oriented Convolutional Neural Network (Mask RCNN), such as ResNET50, ResNet101, and ResNET101 C4, to assess a range of dental radiographs. This technology improves dentists' ability to properly identify filling levels by creating a pixel-based masking system through training on a wide range of tooth pictures. As a result, this invention greatly aids in accelerating and improving the precision of dental treatments, which in turn helps people with dental issues. Furthermore, this framework may in the future allow robots to carry out dental procedures since it offers the pixel-level details required for the procedure.