Dental identification system based on unwrapped CT images

Abstract

Dental comparison of postmortem (PM) and ante-mortem (AM) radiographs provides one of the best avenues for the forensic identification of human remains. Nevertheless conventional dental comparison is labor-intensive, subjective, and has several inherent drawbacks. This paper presents a semi-automated image analysis system designed to assist the forensic dentist with the task of identifying human remains. This system overcomes the drawbacks of conventional dental comparison because it is based on the comparison of radiograph-like images reconstructed from PM computed tomography (CT) data with AM digitized conventional radiographs. The efficacy of the system is demonstrated using 4 dental CT data sets and 32 digitized bitewing radiographs obtained from routine clinical practice.

A pilot study of an automated personal identification process: Applying machine learning to panoramic radiographs

“… 13 14 The automation of the victim identification process enables its application in mass disasters by computationally comparing anatomical data from AM and PM exams. 15 16 17 Several techniques have been described in the literature for the purpose of forensic identification; among the most frequently used are the analysis of dental conditions (such as the assessment of decayed, missing or filled teeth), the number of teeth present, and reference points in anatomical structures. 18 …”

Human identification through frontal sinus 3D superimposition: Pilot study with Cone Beam Computer Tomography

“…31 As a possible bias, as in any human identification situation, the antemortem exam must be replicated as similarly as possible 1 and through the recording of the deceased, or its remains can present differences that may affect the proposed method. We believe that the presence of mucus, bone fractures, the lack of an internal mucosa and other soft tissue in a dry skull may alter the internal gray scale at the DICOM image.…”

Dental Post-Mortem Computed Tomography for Disaster Victim Identification: A Literature Review

“…Eight articles had aims that were too broad and did not specifically focus on dental CT, hence were excluded [9,10,[11][12][13][14][15][16]24]. Six papers were excluded due to lack of relevance to the aim; as they were either focused on methods to reduce streak artefacts, discrimination of dental fillings with CT, matching software's for dental radiograph comparison or the use of AM laser surface scanning [3,20,21,[34][35][36]. Seven articles were found to be related to age estimation using dental PMCT.…”