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Journal of Medical Systems

, Volume 36, Issue 5, pp 3339–3351 | Cite as

Effective Management of Medical Information Through A Novel Blind Watermarking Technique

  • Sudeb DasEmail author
  • Malay Kumar Kundu
Original Paper

Abstract

Medical Data Management (MDM) domain consists of various issues of medical information like authentication, security, privacy, retrieval and storage etc. Medical Image Watermarking (MIW) techniques have recently emerged as a leading technology to solve the problems associated with MDM. This paper proposes a blind, Contourlet Transform (CNT) based MIW scheme, robust to high JPEG and JPEG2000 compression and simultaneously capable of addressing a range of MDM issues like medical information security, content authentication, safe archiving and controlled access retrieval etc. It also provides a way for effective data communication along with automated medical personnel teaching. The original medical image is first decomposed by CNT. The Low pass subband is used to embed the watermark in such a way that enables the proposed method to extract the embedded watermark in a blind manner. Inverse CNT is then applied to get the watermarked image. Extensive experiments were carried out and the performance of the proposed scheme is evaluated through both subjective and quantitative measures. The experimental results and comparisons, confirm the effectiveness and efficiency of the proposed technique in the MDM paradigm.

Keywords

Digital watermarking Contourlet Compression Medical imaging EHR/PHR DICOM 

Notes

Acknowledgements

The authors thank the editor and the anonymous reviewers for their careful work and valuable suggestions. We would also like to thank Machine Intelligence Unit, Indian Statistical Institute, Kolkata-108 (Internal Academic Project) for providing facilities to carry out this work. We are grateful to Dr. Pradip Kumar Das (Dept. of Radiology, Sonoscan Healthcare (P) Limited, Malda, West Bengal) for the subjective evaluation of the watermarked images.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Machine Intelligence UnitIndian Statistical InstituteKolkata-108India

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