| dc.description.abstract | The rapidly increasing rates of unrecognized dental issues, along with the ongoing barriers
to timely dental health monitoring, have raised the need for the creation of Machine
Learning (ML) based dental systems that are accurate and can be used by both patients
and dental professionals. In an effort to bridge the circuit, a combined Deep Learning
(DL) architecture analysis is implemented, which takes advantage of two imaging sources
that are very different yet complementary: Intraoral Red-Green-Blue (RGB) images for
the monitoring of dental health in general purposes, and panoramic Orthopantomogram
(OPG) radiographs for the support of clinical decisions. The approach is composed of
two specifically designed frameworks that include an RGB-based classification system
that also includes the detection of early cases of dental caries, which is for teeth health
monitoring for public use, and an OPG-based system for conceiving and supporting dentists
in radiograph interpreting as a supporting tool in case of complex patterns in OPG
radiographs. | en_US |
