Identity Concealment When Uploading Pictures of Patients in a Tele-Medicine System

J. Azcarraga, John Zachary Raduban, M. C. Gendrano, A. Azcarraga
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Abstract

Tele-medicine systems run the risk of unauthorized access to medical records, and there is greater possibility for the unlawful sharing of sensitive patient information, including children, and possibly showing their private parts. Aside from violating their right to privacy, such practices discourage patients from subjecting themselves to tele-medicine. The authors thus present an automatic identity concealment system for pictures, the way it is designed in the GetBetter tele-medicine system developed under a WHO/TDR grant. Based on open-source face- and eye-detection algorithms, identity concealment is executed by blurring the eye region of a detected face using pixel shuffling. This method is shown to be not only effective in concealing the identity of the patient, but also in preserving the exact distribution of pixel values in the image. This is useful when subsequent image processing techniques are employed, such as when identifying the type of lesions based on images of the skin.
远程医疗系统上传患者照片时的身份隐藏
远程医疗系统存在未经授权访问医疗记录的风险,非法分享包括儿童在内的敏感患者信息的可能性更大,并可能暴露其隐私部分。除了侵犯他们的隐私权外,这种做法还使病人不愿接受远程医疗。因此,这组作者提出了一种自动识别图像的隐藏系统,这种系统是在世卫组织/TDR资助下开发的GetBetter远程医疗系统中设计的。基于开源的人脸和眼睛检测算法,通过像素变换模糊被检测人脸的眼睛区域来实现身份隐藏。该方法不仅可以有效地隐藏患者的身份,而且可以保持图像中像素值的准确分布。当采用后续图像处理技术时,例如根据皮肤图像识别病变类型时,这是有用的。
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