Privacy protection of patient medical images employing nature inspired computational intelligence based reversible watermarking technique for health informatics systems

Abstract

Privacy protection has been a critical issue in the delivery of medical newlineimages for telemedicine, e-health care and other remote medical systems. The aim newlineof this proposed research work is to implement a secure, reversible, digital newlinewatermarking technique for transmission of medical data remotely in health care newlinesystems. In this research work a novel optimized digital watermarking scheme newlineusing discrete wavelet transform and singular value decomposition using cuckoo newlinesearch algorithm based on Lévy flight for embedding watermark into the grayscale newlinemedical images of the patient is employed. The performance of the proposed newlinealgorithm is evaluated on different grayscale host medical images and a watermark newlinelogo image. The performance of the proposed scheme in terms of peak signal to newlinenoise ratio was remarkably high, with an average of 45.346dB compared to other newlinemethods and the robustness of the proposed technique was tested by applying newlinedifferent attacks and the proposed method achieved an overall average NC value newlineof 0.9438 compared to other intelligent techniques. Experimental results reveal newlinethat the proposed method is capable of achieving superior performance compared newlineto some of the state-of-art schemes in terms of robustness, security and high newlineembedding capacity which is required in the field of telemedicine and e-health newlinecare system. Copyright protection of medical images and its Integrity has become newlineone of the key problems in the field of telemedicine. In this research work a novel newlinerobust watermarking scheme based on firefly algorithm in the transform domain newlineis employed. The watermark embedding and extraction are implemented in the newlinediscrete wavelet transform and singular value decomposition transform domain. newline newline