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",
  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.",
  keywords =     "genetic algorithms, genetic programming, Health care,
                 Integer Wavelet Transform, Reversible watermarking,
                 Medical images",
}

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

Citations