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

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.

Three‐Dimensional Cinematic Rendering to Optimize Visualization of Cerebrovascular Anatomy and Disease in CT Angiography

“…The potential misuse of VR for malevolent purposes such as facial recognition should be considered and public use of 3DCR‐CRC must preserve anonymity in compliance with health insurance portability and accountability act HIPAA. The problem of patient identification from rendered imaging data is neither new nor unique to 3DCR and is the subject of ongoing discussion in the literature 32,33 . The following illustrative cases demonstrate the application of 3DCR‐CRC in our practice.…”

Biological fingerprint using scout computed tomographic images for positive patient identification

“…Patient verification is a crucial means to ascertain the correctness of a patient’s identity. Biometric verification process for healthcare authenticates a patient’s identity in addition to the manual checking conducted by healthcare providers . Biometric identification usually refers to the closed‐set identification of someone whose biological fingerprint is stored in a database .…”

“…7 The term biometrics refers to the use of behavioral and biological characteristics to identify an individual. [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] Biometrics are utilized as a part of either a verification or an identification system. [11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] Biometric verification refers to the authentication of a patient's identity by comparing a biological fingerprint with one prestored in a database.…”

“…Biometric verification process for healthcare authenticates a patient's identity in addition to the manual checking conducted by healthcare providers. [11][12][13][14][15] Biometric identification usually refers to the closed-set identification of someone whose biological fingerprint is stored in a database. [8][9][10] Patient identification is a crucial means to identify unconscious or unknown patients.…”

“…[25][26][27] We have previously reported on the usefulness of biological fingerprints using scout magnetic resonance (MR) images of the brain. 11 In other previous studies, medical image biometrics were reported using chest [19][20][21][22][25][26][27] and knee 23 X-ray images, optical surface images 13 , and patient X-ray images 24 acquired during a radiotherapy set-up process, facial images 15 extracted from computed tomography (CT), and facial images 12,14 acquired with mobile camera. Biometrics for healthcare preferred to be a simple process to enable identity verification under various patient conditions [1][2][3][4][5] .…”