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PDE based scheme for multi-modal medical image watermarking

Overview of attention for article published in BioMedical Engineering OnLine, November 2015
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Title
PDE based scheme for multi-modal medical image watermarking
Published in
BioMedical Engineering OnLine, November 2015
DOI 10.1186/s12938-015-0101-x
Pubmed ID
Authors

N. Aherrahrou, H. Tairi

Abstract

This work deals with copyright protection of digital images, an issue that needs protection of intellectual property rights. It is an important issue with a large number of medical images interchanged on the Internet every day. So, it is a challenging task to ensure the integrity of received images as well as authenticity. Digital watermarking techniques have been proposed as valid solution for this problem. It is worth mentioning that the Region Of Interest (ROI)/Region Of Non Interest (RONI) selection can be seen as a significant limitation from which suffers most of ROI/RONI based watermarking schemes and that in turn affects and limit their applicability in an effective way. Generally, the ROI/RONI is defined by a radiologist or a computer-aided selection tool. And thus, this will not be efficient for an institute or health care system, where one has to process a large number of images. Therefore, developing an automatic ROI/RONI selection is a challenge task. The major aim of this work is to develop an automatic selection algorithm of embedding region based on the so called Partial Differential Equation (PDE) method. Thus avoiding ROI/RONI selection problems including: (1) computational overhead, (2) time consuming, and (3) modality dependent selection. The algorithm is evaluated in terms of imperceptibility, robustness, tamper localization and recovery using MRI, Ultrasound, CT and X-ray grey scale medical images. From experimental results that we have conducted on a database of 100 medical images of four modalities, it can be inferred that our method can achieve high imperceptibility, while showing good robustness against attacks. Furthermore, the experiment results confirm the effectiveness of the proposed algorithm in detecting and recovering the various types of tampering. The highest PSNR value reached over the 100 images is 94,746 dB, while the lowest PSNR value is 60,1272 dB, which demonstrates the higher imperceptibility nature of the proposed method. Moreover, the Normalized Correlation (NC) between the original watermark and the corresponding extracted watermark for 100 images is computed. We get a NC value greater than or equal to 0.998. This indicates that the extracted watermark is very similar to the original watermark for all modalities. The key features of our proposed method are to (1) increase the robustness of the watermark against attacks; (2) provide more transparency to the embedded watermark. (3) provide more authenticity and integrity protection of the content of medical images. (4) provide minimum ROI/RONI selection complexity.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 3 17%
Professor 3 17%
Student > Master 3 17%
Student > Ph. D. Student 2 11%
Student > Bachelor 1 6%
Other 2 11%
Unknown 4 22%
Readers by discipline Count As %
Computer Science 3 17%
Engineering 3 17%
Mathematics 1 6%
Business, Management and Accounting 1 6%
Agricultural and Biological Sciences 1 6%
Other 3 17%
Unknown 6 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 November 2015.
All research outputs
#3,145,480
of 6,606,474 outputs
Outputs from BioMedical Engineering OnLine
#142
of 386 outputs
Outputs of similar age
#131,056
of 250,047 outputs
Outputs of similar age from BioMedical Engineering OnLine
#6
of 20 outputs
Altmetric has tracked 6,606,474 research outputs across all sources so far. This one is in the 29th percentile – i.e., 29% of other outputs scored the same or lower than it.
So far Altmetric has tracked 386 research outputs from this source. They receive a mean Attention Score of 2.6. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 250,047 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.