Affiliation:
1. De La Salle University, Manila, Philippines
2. National Telehealth Center, University of the Philippines, Manila, Philippines
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.
Reference46 articles.
1. American Osteopathic College of Dermatology (AOCD). (2016, August 22). Retrieved from http://www.aocd.org/
2. Medical image security in a HIPAA mandated PACS environment
3. Cloudinary. (n.d.). Automatic face-blurring in images made easy. Retrieved from http://cloudinary.com/blog/automatic_face_blurring_in_images_made_easy
4. Cone, S., Rodas, E. J., & Merrell, R. C. (2009). Telemedical support for surgeons in Equador. In R. Wootton, N. G. Patil, R. E. Scott, & K. Ho (Eds.), Telehealth in the Developing World (pp. 193-202). The Royal Society of Medicine Press Ltd.
5. Analysis of skin color models for face detection.;M.Daithankar;International Conference on Communications and Signal Processing (ICCSP),2013