A Tri-level segmented Convolutional Neural Network to predict dental informatics from tooth radiographs - extends to forensic Odontology

The investigation of the scientific composition and conditions in teeth is called odontology. The use of dental evidence in both civil and criminal cases is known as forensic odontology. This can involve recognizing sexual assault, personally identifying the deceased, particularly in a mass catastrophe or when facial recognition is unreliable, or figuring out the ages of unidentified victims. Forensic dentistry uses traditional methods to keep dental records, perform dental imaging, examine bite marks, and endoscopy. There are four different sorts of radiography images that are utilized. The upper and lower teeth are visible in one view on a bitewing radiograph, which is used in routine dental examinations. The entire mouth, including the tissues and their structures, is captured in a panoramic radiograph, a 2D dental examination. The whole tooth is seen on a periapical radiograph, from the crown to the root tip. The side view of the face can be radiographically captured using a cephalometric radiograph. Here Tri-level segmented images using CNN are generated for the extension of forensic odontology.