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Abstract
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.
Highlights
Natural disasters, terrorist attacks, war, severe accidents, migration, or homelessness can result in the discovery of unknown deceased individuals [1, 2]
For each identity from 10 virtual autopsies, 25 postmortem Computed tomography (CT) images showing the maxillary sinus were matched with an antemortem computer vision (CV) database containing 60,255 CV features sets from 853 examinations of 738 identities
This study demonstrates the feasibility of CV-based personal identification using postmortem CT images of the maxillary sinuses, achieving an identification rate of 50% at rank 1, 80% at rank 2, and 100% at rank 7 across 10 identification procedures and 738 potential identities
Summary
Terrorist attacks, war, severe accidents, migration, or homelessness can result in the discovery of unknown deceased individuals [1, 2] In these cases, identification can be a significant challenge. A new personal identification method [10] based on computer vision (CV) has demonstrated success in identifying individuals using single CT slices, by analyzing the maxillary sinuses. This approach extracts distinctive features from cranial CT images - patterns that are unique to each individual. The number of matching points indicates the likelihood that the unknown individual corresponds to a specific identity in the database While effective, this method has so far been applied only to comparisons of antemortem data and relies on individual CT slices rather
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