A new approach to fully-reversible watermarking in medical imaging with breakthrough visibility parameters

Authors: Ales Rocek, Karel Slavicek, Otto Dostal, Michal Javorník


Securing of medical images against intentional or accidental modification is a general issue in modern radiology. Watermarking, with its data-centric security, is very convenient for this purpose. We proposed a new method of fully reversible watermarking in medical imaging by combining the advantages of three traditional approaches—Reversible, Zero and RONI watermarking. The new method achieves exceptionally high values of Peak Signal to Noise Ratio and Structural Similarity index. The article evaluates the pros and cons of current methods of watermarking in medical imaging. Keeping the pros and eliminating the cons of the methods allows a new approach. Specific methods are selected and their application in practice described in detail. Application of the proposed method on a database of 6000 medical images from common hospital operations delivers very promising results which are discussed at the end of the article.


Communication; DICOM; Medical images; Security; Watermarking; Visual cryptography; RONI

Citation: Ales Rocek, Karel Slavicek, Otto Dostal, Michal Javorník A new approach to fully-reversible watermarking in medical imaging with breakthrough visibility parameters http://dx.doi.org/10.1016/j.bspc.2016.05.005

Received: 11 February 2016, Revised: 19 April 2016, Accepted: 19 May 2016, Available online: 10 June 2016

Copyright: © 2016 The Authors. Published by Elsevier Ltd. This is a open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).


This article describes a unique method of securing digital medical images that achieves exceptional results. The method combines the zero distortion of Zero-watermarking in ROI with the high capacity of Reversible watermarking in RONI. The average value of PSNR in images from the test database of 6000 medical images was 81, when RONI was 10% of the image size. In some cases, PSNR even exceeded 105. Another parameter, SSIM, which takes into account human perception of images, averages 0.999974. In the literature, we were unable to trace any watermarking method that achieved similar parameters and did not require storing additional information outside of the image itself. A comparison of the proposed method with other watermarking methods, which use separation of ROI and RONI, shows promising results.

Our next step will be a test on a larger medical image database, which will be ten times bigger, with images from various areas of medicine used in common hospital operation. This method eliminates the principal disadvantages of two common methods by carefully combining them in a way which can be fully automated. We will work to bring this method into practice.


This research was supported by FIONA Eureka LF14035. Computational resources were provided by the CERIT Scientific Cloud LM2015085