Digital Imaging Technologies for Forensic Orofacial Identification: A Systematic Review and Research Agenda

This systematic review critically examines the use of 2D and 3D digital imaging technologies of the face and teeth, with and without integration of artificial intelligence, for human identification in forensic and medicolegal contexts. Following PRISMA 2020 guidelines, Scopus, PubMed and Web of Science were systematically searched, identifying 26 studies published between 2011 and 2025 that met predefined eligibility criteria framed by a PECO-style question. Eighteen studies focused on facial imaging, six on dental imaging and two on integrated orofacial workflows, using digital photography, CCTV/video, 3D surface imaging, intraoral scanners, and three-dimensional superimposition methods, sometimes combined with classical algorithms and deep learning models. In controlled or semi-controlled settings, state-of-the-art facial algorithms often reported very high accuracy, with values up to 99.85%. By contrast, studies using real CCTV or other challenging forensic imagery showed more variable performance, with accuracies ranging from about 72.8% to 96.6%. Dental and orofacial studies reported 100% correct identifications for 3D superimposition of intraoral scans in small samples, and around 83% accuracy for automated AI-based dental identification. Crucially, fulfilling the promise of a true orofacial approach, this review proposes a structured research agenda focused on creating realistic multi-modal databases, standardizing protocols, and implementing probabilistic reporting (likelihood ratios) to guide future validation and legal admissibility.