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16-Bit DICOM Medical Images Lossless Hiding Scheme Based on Edge Sensing Prediction Mechanism

  • Conference paper
Genetic and Evolutionary Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 329))

Abstract

Medical imaging is an important part of patient records. The pixel of a 16-depth DICOM image is totally different from the 8-bit depth nature image and is seldom the same as the other pixels in the nearby area. In this paper, we propose a reversible hiding method that expands Feng and Fan’s prediction technique and adapts the scheme to match the characteristics of medical image. In the previous work, we determine what prediction method should be applied based on standard deviation thresholds to obtain more accurate prediction results. Finally, our approach includes embedding hidden information based on the histogram-shifting technique. The experimental results demonstrate that our approach achieves high-quality results.

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References

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Correspondence to Tzu-Chuen Lu .

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Lu, TC., Tseng, CY., Huang, CC., Deng, KM. (2015). 16-Bit DICOM Medical Images Lossless Hiding Scheme Based on Edge Sensing Prediction Mechanism. In: Sun, H., Yang, CY., Lin, CW., Pan, JS., Snasel, V., Abraham, A. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 329. Springer, Cham. https://doi.org/10.1007/978-3-319-12286-1_19

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  • DOI: https://doi.org/10.1007/978-3-319-12286-1_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12285-4

  • Online ISBN: 978-3-319-12286-1

  • eBook Packages: EngineeringEngineering (R0)

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