New Watermarking/Encryption Method for Medical Imaging FULL Protection in m-Health

In this paper, we present a new method for medical images security dedicated to m-Health based on a combination between a novel semi reversible watermarking approach robust to JPEG compression, a new proposed fragile watermarking and a new proposed encryption algorithm. The purpose of the combination of these three proposed algorithms (encryption, robust and fragile watermarking) is to ensure the full protection of medical image, its information and its report in terms of confidentiality and reliability (authentication and integrity). A hardware implementation to evaluate our system is done using the Texas instrument C6416 DSK card by converting m-files to C/C++ using MATLAB coder. Our m-health security system is then run on the android platform. Experimental results show that the proposed algorithm can achieve high security with good performance

DIGITAL WATERMARKING OF 3D MEDICAL VISUAL OBJECTS

At present, medical equipment provides often 3D models of scanning organs instead of ordinary 2D images. This concept is supported by Digital Imaging and COmmunications in Medicine (DICOM) standard available for telemedicine. This means that the confidential information under transmission ought to be protected by special techniques, particularly digital watermarking scheme instead of textual informative files represented, for example, on CD disks. We propose a multilevel protection, for which a fragile watermark is the first level of protection. The Region Of Interest (ROI) watermark and textual watermarks with information about patient and study (the last ones can be combines as a single textual watermark) form the second level of protection. Encryption of the ROI and textual watermarks using Arnold’s transform is the third level of protection. In the case of 3D models, we find the ROI in each of 2D sliced images, apply the digital wavelet transform or digital shearlet transform (depending on the volume of watermarks) for the ROI and textual watermarks embedding, and embed a fragile watermark using digital Hadamard transform. The main task is to find the relevant regions for embedding. To this and, we develop the original algorithm for selecting relevant regions. The obtained results confirm the robustness of our approach for rotation, scaling, translation, and JPEG attacks

Background matching and disruptive coloration as habitat-specific strategies for camouflage

This is the final version. Available from Nature Research via the DOI in this record.Data availability: All data for this study are included as a supplementary fileCamouflage is a key defence across taxa and frequently critical to survival. A common strategy is background matching, resembling the colour and pattern of the environment. This approach, however, may be ineffective in complex habitats where matching one patch may lead to increased visibility in other patches. In contrast, disruptive coloration, which disguises body outlines, may be effective against complex backgrounds. These ideas have rarely been tested and previous work focuses on artificial systems. Here, we test the camouflage strategies of the shore crab (Carcinus maenas) in two habitats, being a species that is highly variable, capable of plastic changes in appearance, and lives in multiple environments. Using predator (bird and fish) vision modelling and image analysis, we quantified background matching and disruption in crabs from rock pools and mudflats, predicting that disruption would dominate in visually complex rock pools but background matching in more uniform mudflats. As expected, rock pool individuals had significantly higher edge disruption than mudflat crabs, whereas mudflat crabs more closely matched the substrate than rock pool crabs for colour, luminance, and pattern. Our study demonstrates facultative expression of camouflage strategies dependent on the visual environment, with implications for the evolution and interrelatedness of defensive strategies.Biotechnology & Biological Sciences Research Council (BBSRC

Additional information delivery to image content via improved unseen–visible watermarking

In a practical watermark scenario, watermarks are used to provide auxiliary information; in this way, an analogous digital approach called unseen–visible watermark has been introduced to deliver auxiliary information. In this algorithm, the embedding stage takes advantage of the visible and invisible watermarking to embed an owner logotype or barcodes as watermarks; in the exhibition stage, the equipped functions of the display devices are used to reveal the watermark to the naked eyes, eliminating any watermark exhibition algorithm. In this paper, a watermark complement strategy for unseen–visible watermarking is proposed to improve the embedding stage, reducing the histogram distortion and the visual degradation of the watermarked image. The presented algorithm exhibits the following contributions: first, the algorithm can be applied to any class of images with large smooth regions of low or high intensity; second, a watermark complement strategy is introduced to reduce the visual degradation and histogram distortion of the watermarked image; and third, an embedding error measurement is proposed. Evaluation results show that the proposed strategy has high performance in comparison with other algorithms, providing a high visual quality of the exhibited watermark and preserving its robustness in terms of readability and imperceptibility against geometric and processing attacks

Prediction of Proapoptotic Anticancer Therapeutic Response Based on Visualization of Death Ligand-Receptor Interaction and Specific Marker of Cellular Proliferation

Emerging targeted therapeutics hold great promise for the treatment of human cancer. However there are still challenges for selecting patients that most likely will benefit from targeted drugs. One of the major limitations of classical imaging methods is the significant delay to provide quantifiable and objective evidence of response to cancer therapy. Molecular imaging may be useful in targeted drug development by assessing the target expression and drug-target interaction, and predicting therapeutic response in both preclinical and clinical settings. The apoptosis pathway triggered by the Tumor Necrosis Factor (TNF)-Related Apoptosis-Inducing Ligand (TRAIL) receptors is a potential target for therapeutic intervention. TRAIL and its proapoptotic receptor agonistic monoclonal antibodies are being developed as targeted therapeutics in the treatment of human cancer. It is our hypothesis that visualization of proapoptotic receptors and binding of their agonists to proapoptotic receptors can noninvasively predict proapoptotic response if the pathway is intact. Hence the objective of this work is to develop efficient multimodality molecular imaging methods to predict proapoptotic anticancer therapy response before or at the very early stage of treatment. Towards this goal, we have labeled proapoptotic receptor agonists (PARAs) with near-infrared (NIR) fluorescent dyes to image PARAs binding to their targets expressed on the cell surface in cultured cells and in human tumor xenografts grown subcutaneously in immunodeficient mice. Both in vitro and in vivo studies demonstrated that imaging PARAs binding to their targets was well correlated with proapoptotic anticancer therapeutic response when TRAIL signaling pathway was intact. To pursue a more general molecular imaging marker that can predict anticancer therapeutic response even when the signaling pathway is impaired, we explored a novel radiotracer for positron emission tomography (PET) imaging [(18)F]-3\u27-fluoro-3\u27-deoxy-L-thymidine ([(18)F]-FLT), an analogue of thymidine and a specific marker of DNA replication and cellular proliferation. Our results suggested that early changes in [(18)F]-PET may not only predict the tumor histological response to anticancer therapeutics but also determine superiority of one treatment regimen over another. In summary our proof-of-concept studies show that multimodality molecular imaging will greatly aid in accelerating anticancer drug approval process and improving survival and response rates in hard-to-treat cancer

Recent Advances in Signal Processing

The signal processing task is a very critical issue in the majority of new technological inventions and challenges in a variety of applications in both science and engineering fields. Classical signal processing techniques have largely worked with mathematical models that are linear, local, stationary, and Gaussian. They have always favored closed-form tractability over real-world accuracy. These constraints were imposed by the lack of powerful computing tools. During the last few decades, signal processing theories, developments, and applications have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This book is targeted primarily toward both students and researchers who want to be exposed to a wide variety of signal processing techniques and algorithms. It includes 27 chapters that can be categorized into five different areas depending on the application at hand. These five categories are ordered to address image processing, speech processing, communication systems, time-series analysis, and educational packages respectively. The book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Animal vision and colour change for camouflage

Camouflage is a well-studied form of antipredator defence. A key issue is how animals ensure camouflage effectiveness when the visual environments many camouflage strategies rely on vary. Phenotypic plasticity allows animals to adjust coloration to best match such environmental variation. It is assumed that vision is used in identifying this variation and guides changes in colour. However, questions still exist regarding the opportunities and limitations afforded from vision-guided changes for camouflage. Carcinus maenas, the green shore crab, already a widely used species to investigate a variety of questions regarding camouflage, was used to test the assumption that vision is directly responsible for guiding (and limiting) colour change for camouflage. In the first chapter, tests of spectral sensitivity and colour discrimination were performed, which were then compared to colour change responses. Following this, crabs’ spatial resolution was tested and compared to pattern change responses on uniform and patterned backgrounds. Finally, crabs’ brightness change responses to varying illumination and substrate brightness conditions were recorded to examine directional light’s role in substrate perception for plasticity. My results indicate that C. maenas colour change for camouflage is determined and limited by their vision. First, spectral and colour discrimination results indicate C. maenas cannot perceive differences in colour. This aligns with colour change results, with crabs only showing significant achromatic change despite apparently possessing the chromatophores needed for chromatic change. Following this, crab’s changed patterning by increasing pattern contrast proportionate to background pattern size, without changing pattern shape or size. This change in patterning is indicative of a shift from uniform background matching to disruptive markings. Finally, C. maenas colour change corresponds to the relative reflectance of substrates, accounting for illumination. This indicates some level of assessment of directional light, likely dependent on the differential stimulation of an eye perceiving light from multiple directions at once. These results indicate that while species’ vision can limit colour change for camouflage, effective improvements in camouflage are still capable within these limits