Journal of Digital Imaging

, Volume 30, Issue 2, pp 204–214

Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications

Article

DOI: 10.1007/s10278-016-9932-7

Cite this article as:
Parks, C.L. & Monson, K.L. J Digit Imaging (2017) 30: 204. doi:10.1007/s10278-016-9932-7
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Abstract

The recognizability of facial images extracted from publically available medical scans raises patient privacy concerns. This study examined how accurately facial images extracted from computed tomography (CT) scans are objectively matched with corresponding photographs of the scanned individuals. The test subjects were 128 adult Americans ranging in age from 18 to 60 years, representing both sexes and three self-identified population (ancestral descent) groups (African, European, and Hispanic). Using facial recognition software, the 2D images of the extracted facial models were compared for matches against five differently sized photo galleries. Depending on the scanning protocol and gallery size, in 6–61 % of the cases, a correct life photo match for a CT-derived facial image was the top ranked image in the generated candidate lists, even when blind searching in excess of 100,000 images. In 31–91 % of the cases, a correct match was located within the top 50 images. Few significant differences (p > 0.05) in match rates were observed between the sexes or across the three age cohorts. Highly significant differences (p < 0.01) were, however, observed across the three ancestral cohorts and between the two CT scanning protocols. Results suggest that the probability of a match between a facial image extracted from a medical scan and a photograph of the individual is moderately high. The facial image data inherent in commonly employed medical imaging modalities may need to consider a potentially identifiable form of “comparable” facial imagery and protected as such under patient privacy legislation.

Keywords

Facial recognition Patient privacy HIPAA Computed tomography (CT) 

Copyright information

© Society for Imaging Informatics in Medicine 2016

Authors and Affiliations

  1. 1.Counterterrorismand Forensic Science Research Unit, Visiting Scientist Program, FBI Laboratory DivisionQuanticoUSA
  2. 2.Counterterrorism and Forensic Science Research Unit, FBI Laboratory DivisionQuanticoUSA

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