An Optimized Medical Image Watermarking Approach for E-Health Applications

Background: In recent years, information and communication technologies have been widely used in the healthcare sector. This development enables E-Health applications to transmit medical data, as well as their sharing and remote access by healthcare professionals. However, due to their sensitivity, medical data in general, and medical images in particular, are vulnerable to a variety of illegitimate attacks. Therefore, suitable security and effective protection are necessary during transmission. Method: In consideration of these challenges, we put forth a security system relying on digital watermarking with the aim of ensuring the integrity and authenticity of medical images. The proposed approach is based on Integer Wavelet Transform as an embedding algorithm; furthermore, Particles Swarm Optimization was employed to select the optimal scaling factor, which allows the system to be compatible with different medical imaging modalities. Results: The experimental results demonstrate that the method provides a high imperceptibility and robustness for both secret watermark and watermarked images. In addition, the proposed scheme performs better for medical images compared with similar watermarking algorithms. Conclusion: As it is suitable for a lossless-data application, IWT is the best choice for medical images integrity. Furthermore, using the PSO algorithm enables the algorithm to be compatible with different medical imaging modalities

An Investigation of Match for Lossless Video Compression

A new lossless video compression technique, Match, is investigated. Match uses the similarity between the frames of a video or the slices of medical images to find a prediction for the current pixel. A portion of the previous frame is searched to find a matching context, which is the pixels surrounding the current pixel, within some distance centered on the current location. The best distance to use for each dataset is found experimentally. The matching context refers to the neighborhood of w, nw, n, and ne, where the pixel in the previous frame with the closest matching context becomes the prediction. w, nw, n, and ne stand for west, northwest, north, and northeast respectively. Using these directions, w is the pixel to the left of the current one, nw is the pixel to the left and up one row, n is the pixel directly above the current one and ne refers to the pixel up one row and to the right one column. From the prediction, the error is then calculated, remapped and encoded using adaptive arithmetic encoding. Match\u27s resulting compression ratio is then compared to that of CALIC\u27s, where the larger the compression ratio the more efficient the method. CALIC is a context-bases adaptive lossless image compression technique that is regarded as one of the best lossless image compression techniques. Match was evaluated for twenty-two video datasets of varying resolutions as well as 65 C.T. scans and 17 M.R.I. scans. Some common differences amongst videos are resolution and frame rate. Therefore, Match was used to compress four videos with varying resolution to see how Match is affected by resolution and Match was examined on one dataset that had varying frame rate. There were times when Match outperformed CALIC; however, there were also times where CALIC outperformed Match and other times where the two methods resulted in nearly identical compression ratios. Therefore, as a preprocessing step, the structural similarity was examined as well as the edge quality measurements to predict which method, Match or CALIC, results in the best compression. Advisor: Khalid Sayoo

Hybrid Region-based Image Compression Scheme for Mamograms and Ultrasound Images

The need for transmission and archive of mammograms and ultrasound Images has dramatically increased in tele-healthcare applications. Such images require large amount of' storage space which affect transmission speed. Therefore an effective compression scheme is essential. Compression of these images. in general. laces a great challenge to compromise between the higher compression ratio and the relevant diagnostic information. Out of the many studied compression schemes. lossless . IPl. (i- LS and lossy SPII IT are found to he the most efficient ones. JPEG-LS and SI'll IT are chosen based on a comprehensive experimental study carried on a large number of mammograms and ultrasound images of different sizes and texture. The lossless schemes are evaluated based on the compression ratio and compression speed. The distortion in the image quality which is introduced by lossy methods evaluated based on objective criteria using Mean Square Error (MSE) and Peak signal to Noise Ratio (PSNR). It is found that lossless compression can achieve a modest compression ratio 2: 1 - 4: 1. bossy compression schemes can achieve higher compression ratios than lossless ones but at the price of the image quality which may impede diagnostic conclusions. In this work, a new compression approach called Ilvbrid Region-based Image Compression Scheme (IIYRICS) has been proposed for the mammograms and ultrasound images to achieve higher compression ratios without compromising the diagnostic quality. In I LYRICS, a modification for JPI; G-LS is introduced to encode the arbitrary shaped disease affected regions. Then Shape adaptive SPIT IT is applied on the remaining non region of interest. The results clearly show that this hybrid strategy can yield high compression ratios with perfect reconstruction of diagnostic relevant regions, achieving high speed transmission and less storage requirement. For the sample images considered in our experiment, the compression ratio increases approximately ten times. However, this increase depends upon the size of the region of interest chosen. It is also föund that the pre-processing (contrast stretching) of region of interest improves compression ratios on mammograms but not on ultrasound images

A distributed Quadtree Dictionary approach to multi-resolution visualization of scattered neutron data

Grid computing is described as dependable, seamless, pervasive access to resources and services, whereas mobile computing allows the movement of people from place to place while staying connected to resources at each location. Mobile grid computing is a new computing paradigm, which joins these two technologies by enabling access to the collection of resources within a user\u27s virtual organization while still maintaining the freedom of mobile computing through a service paradigm. A major problem in virtual organization is needs mismatch, in which one resources requests a service from another resources it is unable to fulfill, since virtual organizations are necessarily heterogeneous collections of resources. In this dissertation we propose a solution to the needs mismatch problem in the case of high energy physics data. Specifically, we propose a Quadtree Dictionary (QTD) algorithm to provide lossless, multi-resolution compression of datasets and enable their visualization on devices of all capabilities. As a prototype application, we extend the Integrated Spectral Analysis Workbench (ISAW) developed at the Intense Pulsed Neutron Source Division of the Argonne National Laboratory into a mobile Grid application, Mobile ISAW. In this dissertation we compare our QTD algorithm with several existing compression techniques on ISAW\u27s Single-Crystal Diffractometer (SCD) datasets. We then extend our QTD algorithm to a distributed setting and examine its effectiveness on the next generation of SCD datasets. In both a serial and distributed setting, our QTD algorithm performs no worse than existing techniques such as the square wavelet transform in terms of energy conservation, while providing the worst-case savings of 8:1

Design and implementation a prototype system for fusion image by using SWT-PCA algorithm with FPGA technique

The technology of fusion image is dominance strongly over domain research for recent years, the techniques of fusion have various applications in real time used and proposed such as purpose of military and remote sensing etc.,the fusion image is very efficient in processing of digital image. Single image produced from two images or more information of relevant combining process results from multi sensor fusion image. FPGA is the best implementation types of most technology enabling wide spread.This device works with modern versions for different critical characteristics same huge number of elements logic in order to permit complex algorithm implemented. In this paper,filters are designed and implemented in FPGA utilized for disease specified detection from images CT/MRI scanned where the samples are taken for human's brain with various medical images and the processing of fusion employed by using technique Stationary Wavelet Transform and Principal Component Analysis (SWT-PCA). Accuracy image output increases when implemented this technique and that was done by sampling down eliminating where effects blurring and artifacts doesn't influenced. The algorithm of SWT-PCA parameters quality measurements like NCC,MSE ,PSNR, coefficients and Eigen values.The advantages significant of this system that provide real time, time rapid to market and portability beside the change parametric continuing in the DWT transform. The designed and simulation of module proposed system has been done by using MATLAB simulink and blocks generator system, Xilinx synthesized with synthesis tool (XST) and implemented in XilinxSpartan 6-SP605 device

Hybrid Region-based Image Compression Scheme for Mamograms and Ultrasound Images

The need for transmission and archive of mammograms and ultrasound Images has dramatically increased in tele-healthcare applications. Such images require large amount of' storage space which affect transmission speed. Therefore an effective compression scheme is essential. Compression of these images. in general. laces a great challenge to compromise between the higher compression ratio and the relevant diagnostic information. Out of the many studied compression schemes. lossless . IPl. (i- LS and lossy SPII IT are found to he the most efficient ones. JPEG-LS and SI'll IT are chosen based on a comprehensive experimental study carried on a large number of mammograms and ultrasound images of different sizes and texture. The lossless schemes are evaluated based on the compression ratio and compression speed. The distortion in the image quality which is introduced by lossy methods evaluated based on objective criteria using Mean Square Error (MSE) and Peak signal to Noise Ratio (PSNR). It is found that lossless compression can achieve a modest compression ratio 2: 1 - 4: 1. bossy compression schemes can achieve higher compression ratios than lossless ones but at the price of the image quality which may impede diagnostic conclusions. In this work, a new compression approach called Ilvbrid Region-based Image Compression Scheme (IIYRICS) has been proposed for the mammograms and ultrasound images to achieve higher compression ratios without compromising the diagnostic quality. In I LYRICS, a modification for JPI; G-LS is introduced to encode the arbitrary shaped disease affected regions. Then Shape adaptive SPIT IT is applied on the remaining non region of interest. The results clearly show that this hybrid strategy can yield high compression ratios with perfect reconstruction of diagnostic relevant regions, achieving high speed transmission and less storage requirement. For the sample images considered in our experiment, the compression ratio increases approximately ten times. However, this increase depends upon the size of the region of interest chosen. It is also föund that the pre-processing (contrast stretching) of region of interest improves compression ratios on mammograms but not on ultrasound images

Improving Access and Mental Health for Youth Through Virtual Models of Care

The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic

The Impact of Digital Technologies on Public Health in Developed and Developing Countries

This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic