Adaptive reversible watermarking for authentication and privacy protection of medical records

Abstract

Medical systems, such as PACS or scanners, are vulnerable to security and forgery attacks. Consequently, medical records, such as patient information and medical imagery, can be easily leaked or forged. Reversible watermarking is an efficient solution used to protect medical records. However, previous studies have not sufficiently addressed medical applications. This study proposes an adaptive reversible watermarking algorithm that is directly applicable to medical systems that preserves the quality of medical imagery. In particular, the characteristics of medical imagery are considered. Once object and background regions are segmented, the reversible watermarking algorithm is applied based on an estimated error expansion approach. The watermark is embedded by expanding the estimated error from adjacent pixels. This watermark can include patient information or a hash code to detect forgery. When the watermark is extracted, original imagery is perfectly reconstructed without any quality degradation. Inherent over- and underflow problems are solved using an error pre-compensation technique. With the use of medical images from MRI, CT, and X-ray scanners, intensive experiments are performed to analyze the performance of the proposed algorithm with respect to capacity, perceptual quality, and reconstruction rate.