Reversible and imperceptible watermarking approach for ensuring the integrity and authenticity of brain MR images

The digital medical workflow has many circumstances in which the image data can be manipulated both within the secured Hospital Information Systems (HIS) and outside, as images are viewed, extracted and exchanged. This potentially grows ethical and legal concerns regarding modifying images details that are crucial in medical examinations. Digital watermarking is recognised as a robust technique for enhancing trust within medical imaging by detecting alterations applied to medical images. Despite its efficiency, digital watermarking has not been widely used in medical imaging. Existing watermarking approaches often suffer from validation of their appropriateness to medical domains. Particularly, several research gaps have been identified: (i) essential requirements for the watermarking of medical images are not well defined; (ii) no standard approach can be found in the literature to evaluate the imperceptibility of watermarked images; and (iii) no study has been conducted before to test digital watermarking in a medical imaging workflow. This research aims to investigate digital watermarking to designing, analysing and applying it to medical images to confirm manipulations can be detected and tracked. In addressing these gaps, a number of original contributions have been presented. A new reversible and imperceptible watermarking approach is presented to detect manipulations of brain Magnetic Resonance (MR) images based on Difference Expansion (DE) technique. Experimental results show that the proposed method, whilst fully reversible, can also realise a watermarked image with low degradation for reasonable and controllable embedding capacity. This is fulfilled by encoding the data into smooth regions (blocks that have least differences between their pixels values) inside the Region of Interest (ROI) part of medical images and also through the elimination of the large location map (location of pixels used for encoding the data) required at extraction to retrieve the encoded data. This compares favourably to outcomes reported under current state-of-art techniques in terms of visual image quality of watermarked images. This was also evaluated through conducting a novel visual assessment based on relative Visual Grading Analysis (relative VGA) to define a perceptual threshold in which modifications become noticeable to radiographers. The proposed approach is then integrated into medical systems to verify its validity and applicability in a real application scenario of medical imaging where medical images are generated, exchanged and archived. This enhanced security measure, therefore, enables the detection of image manipulations, by an imperceptible and reversible watermarking approach, that may establish increased trust in the digital medical imaging workflow

Non-Integrative Lentivirus Drives High-Frequency cre-Mediated Cassette Exchange in Human Cells

Recombinase mediated cassette exchange (RMCE) is a two-step process leading to genetic modification in a specific genomic target sequence. The process involves insertion of a docking genetic cassette in the genome followed by DNA transfer of a second cassette flanked by compatible recombination signals and expression of the recombinase. Major technical drawbacks are cell viability upon transfection, toxicity of the enzyme, and the ability to target efficiently cell types of different origins. To overcome such drawbacks, we developed an RMCE assay that uses an integrase-deficient lentivirus (IDLV) vector in the second step combined with promoterless trapping of double selectable markers. Additionally, recombinase expression is self-limiting as a result of the exchangeable reaction, thus avoiding toxicity. Our approach provides proof-of-principle of a simple and novel strategy with expected wide applicability modelled on a human cell line with randomly integrated copies of a genetic landing pad. This strategy does not present foreseeable limitations for application to other cell systems modified by homologous recombination. Safety, efficiency, and simplicity are the major advantages of our system, which can be applied in low-to-medium throughput strategies for screening of cDNAs, non-coding RNAs during functional genomic studies, and drug screening

Efficacy of a 7-day course of furazolidone, levofloxacin, and lansoprazole after failed Helicobacter pylori eradication

<p>Abstract</p> <p>Background</p> <p>Increasing resistance to clarithromycin and nitroimidazole is the main cause of failure in the <it>Helicobacter pylori </it>eradication. The ideal retreatment regimen remains unclear, especially in developing countries, where the infection presents high prevalence and resistance to antibiotics. The study aimed at determining the efficacy, compliance and adverse effects of a regimen that included furazolidone, levofloxacin and lansoprazole in patients with persistent <it>Helicobacter pylori </it>infection, who had failed to respond to at least one prior eradication treatment regimen.</p> <p>Methods</p> <p>This study included 48 patients with peptic ulcer disease. <it>Helicobacter pylori </it>infection was confirmed by a rapid urease test and histological examination of samples obtained from the antrum and corpus during endoscopy. The eradication therapy consisted of a 7-day twice daily oral administration of lansoprazole 30 mg, furazolidone 200 mg and levofloxacin 250 mg. Therapeutic success was confirmed by a negative rapid urease test, histological examination and 14C- urea breath test, performed 12 weeks after treatment completion. The Chi-square method was used for comparisons among eradication rates, previous treatments and previous furazolidone use.</p> <p>Results</p> <p>Only one of the 48 patients failed to take all medications, which was due to adverse effects (vomiting). Per-protocol and intention-to-treat eradication rates were 89% (95% CI- 89%–99%) and 88% (88–92%), respectively. Mild and moderate adverse effects were reported by 41 patients (85%). For patients with one previous treatment failure, the eradication rate was 100%. Compared to furazolidone-naïve patients, eradication rates were lower in those who had failed prior furazolidone-containing regimen(s) (74% vs. 100%, p = 0.002).</p> <p>Conclusion</p> <p>An empiric salvage-regimen including levofloxacin, furazolidone and lansoprazole is very effective in the eradication of <it>Helicobacter pylori</it>, particularly in patients that have failed one prior eradication therapy.</p

Transparency and Trust in Human-AI-Interaction: The Role of Model-Agnostic Explanations in Computer Vision-Based Decision Support

Computer Vision, and hence Artificial Intelligence-based extraction of information from images, has increasingly received attention over the last years, for instance in medical diagnostics. While the algorithms' complexity is a reason for their increased performance, it also leads to the "black box" problem, consequently decreasing trust towards AI. In this regard, "Explainable Artificial Intelligence" (XAI) allows to open that black box and to improve the degree of AI transparency. In this paper, we first discuss the theoretical impact of explainability on trust towards AI, followed by showcasing how the usage of XAI in a health-related setting can look like. More specifically, we show how XAI can be applied to understand why Computer Vision, based on deep learning, did or did not detect a disease (malaria) on image data (thin blood smear slide images). Furthermore, we investigate, how XAI can be used to compare the detection strategy of two different deep learning models often used for Computer Vision: Convolutional Neural Network and Multi-Layer Perceptron. Our empirical results show that i) the AI sometimes used questionable or irrelevant data features of an image to detect malaria (even if correctly predicted), and ii) that there may be significant discrepancies in how different deep learning models explain the same prediction. Our theoretical discussion highlights that XAI can support trust in Computer Vision systems, and AI systems in general, especially through an increased understandability and predictability

Performance Comparison of Intelligent Techniques Based Image Watermarking

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Grammatical translation errors in the ist times bilingual newspaper from Indonesian into English

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Grammatical translation errors in the ist times bilingual newspaper from Indonesian into English

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80 tahun Prof. Dr. Maftuchah Yusuf : mencipta generasi, membangun bangsa

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