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Deidentification of facial images using composites

Mark E. Engelstad; Molly McClellan; Julie A. Jacko; Genevieve B. Melton (Profiled Author: Mark Engelstad)

Journal of Oral and Maxillofacial Surgery. 2011;69(12):3026-3031.

Abstract

Purpose: Maxillofacial surgeons rely on photography for education and documentation. Photographs of the face, unlike those of other body regions, are readily identifiable. Traditional methods of facial image deidentification decrease educational quality or fail to adequately conceal identity. In the present study, a method that uses blended facial composites to deidentify original facial images was developed. This method allows significant components of the original face to be visualized while concealing its identity. Materials and Methods: The method was used to develop 20 different composite facial images that were viewed by student subjects. Ten of these images contained at least one third of a face that was familiar to the subjects. Subjects viewed the composite faces twicefirst unaware that the faces were composites, and then primed to the presence of composites. Subjects later rated the efficacy of this method for image deidentification. Results: When unaware that they were viewing composite images, no subjects recognized the familiar faces within the composites or rated them as familiar (0/120 total views, 0%). When later primed to the potential presence of familiar faces within composites, the identification rate increased significantly (74/120, 62%; P <.001). Results were similar no matter which portion of the familiar face (upper, 67%; mid, 54%; lower, 67%) was present. Subjects rated all composites as clinically realistic patient images. They also rated composites as more effective at deidentification than traditional methods. Conclusion: The use of composites appears to be a promising concept for facial image deidentification. Further larger-scale studies are needed to validate these findings. © 2011 American Association of Oral and Maxillofacial Surgeons.


PMID: 21601340    

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