Automated identification of unknown decedents: matching postmortem CT images with clinical databases

The maxillary sinus plays an important role in the forensic identification of unknown deceased individuals. This study aimed to evaluate whether matching postmortem computed tomography (CT) images from virtual autopsies with antemortem CT examinations from a clinical database enables reliable identification using computer vision (CV) techniques. From ten virtual autopsies, CT images of the maxillary sinus were selected for comparison against 853 antemortem CT examinations from 738 individuals. A total of 60,255 antemortem CT slices underwent image processing, CV feature extraction, and were stored in an antemortem CV database. The number of matching points between CV features of the postmortem image and the antemortem reference image served as an indicator of identification accuracy. The identification rate was 50% (5/10) at rank 1 (with the sought identity having the highest number of matching points), 80% (8/10) at rank 2, and 100% (10/10) at rank 7 among the 738 potential identities. Challenges were observed when the antemortem reference CT examination depicted only parts of the maxillary sinus or when injuries were present. Additionally, postmortem imaging should closely replicate antemortem imaging standards to maximize the number of CV matching points. In conclusion, the findings suggest that it is feasible to identify individuals using postmortem CT images from virtual autopsies in combination with a clinical database. However, postmortem imaging should ideally adhere to clinical imaging standards to achieve more CV matching points for the sought identity with the antemortem reference.