title: Synthesizing dental radiographs for human identification.
abstract: The task of identifying human remains based on dental comparisons of post mortem (PM) and ante mortem (AM) radiographs is labor-intensive, subjective, and has several drawbacks, including: inherently poor image quality, difficulty matching the viewing angles in PM radiographs to those taken AM, and the fact that the state of the dental remains may entirely preclude the possibility of obtaining certain types of radiographs PM. The aim of the present study was to investigate the feasibility of using radiograph-like images reconstructed from PM x-ray computed tomography (CT) data to overcome the shortcomings of conventional radiographic comparison. Algorithms for computer synthesis of panoramic, periapical, and bitewing images are presented. The algorithms were evaluated with data from clinical examinations of two persons. The results demonstrate the efficacy of the CT-based approach and that, in comparison with conventional radiographs, the synthesized images exhibit minimal geometric distortion, reduced blurring, and reduced superimposition of oral structures.
authors.affiliation: School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane QLD 4072, Australia.
authors.forename: S
authors.initials: S
authors.lastname: Tohnak
authors.forename: A J H
authors.initials: AJ
authors.lastname: Mehnert
authors.forename: M
authors.initials: M
authors.lastname: Mahoney
authors.forename: S
authors.initials: S
authors.lastname: Crozier
mesh_terms: D000465:Algorithms; D018732:Forensic Anthropology / Q000379:methods*; D005553:Forensic Dentistry / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods; D011856:Radiographic Image Enhancement / Q000379:methods*; D011861:Radiography, Dental / Q000379:methods*; D014057:Tomography, X-Ray Computed