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基于容积渲染磁共振成像数据的面部识别。

Facial recognition from volume-rendered magnetic resonance imaging data.

作者信息

Prior Fred W, Brunsden Barry, Hildebolt Charles, Nolan Tracy S, Pringle Michael, Vaishnavi S Neil, Larson-Prior Linda J

机构信息

Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA.

出版信息

IEEE Trans Inf Technol Biomed. 2009 Jan;13(1):5-9. doi: 10.1109/TITB.2008.2003335.

Abstract

Three-dimensional (3-D) reconstructions of computed tomography (CT) and magnetic resonance (MR) brain imaging studies are a routine component of both clinical practice and clinical and translational research. A side effect of such reconstructions is the creation of a potentially recognizable face. The Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule requires that individually identifiable health information may not be used for research unless identifiers that may be associated with the health information including "Full face photographic images and other comparable images ..." are removed (de-identification). Thus, a key question is: Are reconstructed facial images comparable to full-face photographs for the purpose of identification? To address this question, MR images were selected from existing research repositories and subjects were asked to pair an MR reconstruction with one of 40 photographs. The chance probability that an observer could match a photograph with its 3-D MR image was 1 in 40 (0.025), and we considered 4 successes out of 40 (4/40, 0.1) to indicate that a subject could identify persons' faces from their 3-D MR images. Forty percent of the subjects were able to successfully match photographs with MR images with success rates higher than the null hypothesis success rate. The Blyth-Still-Casella 95% confidence interval for the 40% success rate was 29%-52%, and the 40% success rate was significantly higher ( P < 0.001) than our null hypothesis success rate of 1 in 10 (0.10).

摘要

计算机断层扫描(CT)和磁共振(MR)脑部成像研究的三维(3-D)重建是临床实践以及临床与转化研究的常规组成部分。这种重建的一个副作用是会生成一张可能被识别出的脸。1996年的《健康保险流通与责任法案》(HIPAA)隐私规则要求,除非去除可能与健康信息相关的标识符,包括“全脸照片图像及其他类似图像……”,否则不得将可识别个人身份的健康信息用于研究(去识别化)。因此,一个关键问题是:就识别目的而言,重建的面部图像与全脸照片是否具有可比性?为解决这个问题,从现有的研究资料库中选取了MR图像,并要求受试者将一张MR重建图像与40张照片中的一张进行配对。观察者将照片与其3-D MR图像匹配成功的概率为40分之一(0.025),我们认为在40次配对中有4次成功(4/40,0.1)表明受试者能够从其3-D MR图像中识别出人脸。40%的受试者能够成功地将照片与MR图像配对,成功率高于零假设成功率。40%成功率的布莱思-斯蒂尔-卡塞拉95%置信区间为29%-52%,且40%的成功率显著高于我们10分之一(0.10)的零假设成功率(P<0.001)。

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