Content-independent embedding scheme for multi-modal medical image watermarking

Abstract

BackgroundAs the increasing adoption of information technology continues to offer better distant medical services, the distribution of, and remote access to digital medical images over public networks continues to grow significantly. Such use of medical images raises serious concerns for their continuous security protection, which digital watermarking has shown great potential to address.MethodsWe present a content-independent embedding scheme for medical image watermarking. We observe that the perceptual content of medical images varies widely with their modalities. Recent medical image watermarking schemes are image-content dependent and thus they may suffer from inconsistent embedding capacity and visual artefacts. To attain the image content-independent embedding property, we generalise RONI (region of non-interest, to the medical professionals) selection process and use it for embedding by utilising RONI’s least significant bit-planes. The proposed scheme thus avoids the need for RONI segmentation that incurs capacity and computational overheads.ResultsOur experimental results demonstrate that the proposed embedding scheme performs consistently over a dataset of 370 medical images including their 7 different modalities. Experimental results also verify how the state-of-the-art reversible schemes can have an inconsistent performance for different modalities of medical images. Our scheme has MSSIM (Mean Structural SIMilarity) larger than 0.999 with a deterministically adaptable embedding capacity.ConclusionsOur proposed image-content independent embedding scheme is modality-wise consistent, and maintains a good image quality of RONI while keeping all other pixels in the image untouched. Thus, with an appropriate watermarking framework (i.e., with the considerations of watermark generation, embedding and detection functions), our proposed scheme can be viable for the multi-modality medical image applications and distant medical services such as teleradiology and eHealth.

Content Preserving Watermarking for Medical Images Using Shearlet Transform and SVD

“…Therefore, the border areas as the RONI are the container for data embedding. Nyeem et al (Nyeem et al, 2015) formulated the RONI selection criteria in a following manner:…”

Concise analysis of current text automation and watermarking approaches

“…Achieving all of these properties with one watermarking system is not practicable. Considering the application domain, all watermarking methods choose some of them and give up the others .…”

Watermarking Capacity Control for Dynamic Payload Embedding

“…We analyse and experiment with the Nyeem, Boles, and Boyd (or NBB) scheme [22,23] and Hu, Lee, and Li (or HLL) scheme [11] below as to determine the performance of their capacity control for dynamic payload embedding. The choice of the HLL scheme is made as it is a prominent watermarking scheme having capacity control that closely represents the existing capacity control scenario, as mentioned in Sec.…”

“…The NBB Scheme Analysis NBB scheme [22,23] is proposed to provide continuous security protection and to minimize the legal-ethical issues of medical images. That scheme embeds payloads in the LSB (least significant bit) planes of the border pixels of input images.…”