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计算机断层扫描衍生面部图像的自动面部识别:对患者隐私的影响

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

作者信息

Parks Connie L, Monson Keith L

机构信息

Counterterrorismand Forensic Science Research Unit, Visiting Scientist Program, FBI Laboratory Division, 2501 Investigation Parkway, Quantico, VA, 22135, USA.

Counterterrorism and Forensic Science Research Unit, FBI Laboratory Division, 2501 Investigation Parkway, Quantico, VA, 22135, USA.

出版信息

J Digit Imaging. 2017 Apr;30(2):204-214. doi: 10.1007/s10278-016-9932-7.

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.

摘要

从公开的医学扫描中提取的面部图像的可识别性引发了患者隐私问题。本研究调查了从计算机断层扫描(CT)中提取的面部图像与被扫描个体的相应照片进行客观匹配的准确性。测试对象为128名年龄在18至60岁之间的成年美国人,涵盖了男女两性以及三个自我认定的人群(祖籍)组(非洲裔、欧洲裔和西班牙裔)。使用面部识别软件,将提取的面部模型的二维图像与五个不同大小的照片库进行匹配比较。根据扫描协议和照片库大小,在6%至61%的情况下,即使在超过10万张图像中进行盲目搜索,CT衍生面部图像的正确生活照片匹配在生成的候选列表中也是排名第一的图像。在31%至91%的情况下,正确匹配位于前50张图像之内。在性别之间或三个年龄组中,匹配率几乎没有显著差异(p>0.05)。然而,在三个祖籍组之间以及两种CT扫描协议之间观察到了高度显著的差异(p<0.01)。结果表明,从医学扫描中提取的面部图像与个体照片之间匹配的概率适中偏高。常用医学成像模式中固有的面部图像数据可能需要考虑一种潜在可识别形式的“可比”面部图像,并根据患者隐私立法进行保护。

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