Protecting Patient Privacy against Unauthorized Release of Medical Images Using Weighted Quantum Particle Swarm Optimization Algorithm

Citation:
Al-Shammari, E. T., A. E. Hassanien, and O. Saleh, "Protecting Patient Privacy against Unauthorized Release of Medical Images Using Weighted Quantum Particle Swarm Optimization Algorithm", 2nd IAPR Asian Conference on Pattern Recognition (ACPR), pp 667- 671, Okinawa, Japan, 2013.

Date Presented:

2013

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In this article, we propose an authentication approach for protecting patient privacy against unauthorized release of medical images using weighted quantum particle swarm optimization algorithm. The weighted quantum particle swarm optimization algorithm adapted to determine the proper quantization step that was used to embed patient fingerprint digital digest bits into the singular values vector of each block of the host medical image. The extracted minutiae points from a patient fingerprint are represented by a fixed length code vector, called bio-minutiae fingerprint code and does not assume a prealignment between the test and the stored fingerprint templates. The principal curves algorithm were used to extract the minutiae points from the fingerprint, then using the systematic biohash function to compute the digital digest. Then, the digital digest was embedded using discrete cosine transform. Then, the watermarked patient's medical image is transmitted to the receiver side. The experimental results show that the proposed authentication approach is confirmed as robust against a wide variety of common attacks.

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