Artificial intelligence and skull imaging advancements in forensic identification

Managing the massive losses associated with large-scale disasters requires significant resources. The unexpected violence of these events generally remains a matter of casualties that urgently need to be identified in a reliable and cost-effective manner. To overcome these difficulties, many researchers have attempted to develop automated methods; moreover, a few recent research have investigated the applicability of artificial intelligence (AI)-based methods using skull, dental, and maxillofacial forensic imaging. In this review, we speculate on the advancement and potential of AI in Dental and Maxillofacial imaging that can help simplify person or victim identification and speed up the process with good accuracy. Using a few prefix search phrases, an online literature search was conducted (AI, Forensic, Skull, Dental, Imaging, Radiology) to identify papers about the advancement of AI in forensic dentistry in all kinds of radiographs, including two-dimensional (2D) and three-dimensional (3D) radiographs, cone beam computed tomography (CT) and CT. Most of the studies reported that automated methods of human identification based on 2D and 3D Dental and Skull radiographs using a convolutional neural network showed to assist in the fast and accurate identification by expertise evaluating a lot of images and quickly coming up with potential matches for identification. We advocate the application of AI techniques in the identification of individuals. However, there is a need to continue research with emphasis to validate models in skull identification.