Reversible Anonymization of DICOM Images using Cryptography and Digital Watermarking

Abstract: Digital Imaging and Communications in Medicine (DICOM) is a standard for handling, storing, printing, and transmitting information in medical images. The DICOM file contains the image data and a number of attributes such as identified patient data (name, age, insurance ID card,…), and non-identified patient data (doctor’s interpretation, image type,…). Medical images serve not only for examination, but can also be used for research and education purposes. For research they are used to prevent illegal use of information; before authorizing researchers to use these images, the medical staff deletes all the data which would reveal the patient identity to prevent patient privacy. This manipulation is called anonymization. In this paper, we propose a reversible anonymization of DICOM images. Identifying patient data with image digest, computed by the well-known SHA-256 hash function, are encrypted using the proposed probabilistic public key crypto-system. After compressing the Least Significant Bit (LSB) bitplan of the image using Hofmann coding algorithm, the encrypted data is inserted into a liberated zone of the LSB bitplan of the image. The proposed method allows researchers to use anonymous DICOM images and keep to authorized staff -if necessary- the possibility to return to the original image with all related patient data.

Youssef ZAZ and Lhoussain ELFADIL. “Reversible Anonymization of DICOM Images using Cryptography and Digital Watermarking”. International Journal of Advanced Computer Science and Applications (IJACSA) 3.4 (2012). http://dx.doi.org/10.14569/IJACSA.2012.030414

@article{ZAZ2012,
title = {Reversible Anonymization of DICOM Images using Cryptography and Digital Watermarking},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2012.030414},
url = {http://dx.doi.org/10.14569/IJACSA.2012.030414},
year = {2012},
publisher = {The Science and Information Organization},
volume = {3},
number = {4},
author = {Youssef ZAZ and Lhoussain ELFADIL}
}