Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique

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@Article{Arsalan:2017:ASC,

• author = "Muhammad Arsalan and Aqsa Saeed Qureshi and Asifullah Khan and Muttukrishnan Rajarajan",
• title = "Protection of medical images and patient related information in healthcare: Using an intelligent and reversible watermarking technique",
• journal = "Applied Soft Computing",
• volume = "51",
• pages = "168--179",
• year = "2017",
• month = feb,
• keywords = "genetic algorithms, genetic programming, Health care, Integer Wavelet Transform, Reversible watermarking, Medical images",
• ISSN = "1568-4946",
• DOI = "doi:10.1016/j.asoc.2016.11.044",
• URL = "http://www.sciencedirect.com/science/article/pii/S1568494616306135",
• abstract = "This work presents an intelligent technique based on reversible watermarking for protecting patient and medical related information. In the proposed technique IRW-Med, the concept of companding function is exploited for reducing embedding distortion, while Integer Wavelet Transform (IWT) is used as an embedding domain for achieving reversibility. Histogram processing is employed to avoid underflow/overflow. In addition, the learning capabilities of Genetic Programming (GP) are exploited for intelligent wavelet coefficient selection. In this context, GP is used to evolve models that not only make an optimal tradeoff between imperceptibility and capacity of the watermark, but also exploit the wavelet coefficient hidden dependencies and information related to the type of sub band. The novelty of the proposed IRW-Med technique lies in its ability to generate a model that can find optimal wavelet coefficients for embedding, and also acts as a companding factor for watermark embedding. The proposed IRW-Med is thus able to embed watermark with low distortion, take out the hidden information, and also recovers the original image. The proposed IRW-Med technique is effective with respect to capacity and imperceptibility and effectiveness is demonstrated through experimental comparisons with existing techniques using standard images as well as a publically available medical image dataset.",

}

Genetic Programming entries for Muhammad Arsalan Awan Aqsa Saeed Qureshi Asifullah Khan Muttukrishnan Rajarajan

Citations