M-Health: Emerging Mobile Health Systems

Springer Science & Business Media
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M-health can be defined as the ‘emerging mobile communications and network technologies for healthcare systems.' This book paves the path toward understanding the future of m-health technologies and services and also introducing the impact of mobility on existing e-health and commercial telemedical systems. M-Health: Emerging Mobile Health Systems presents a new and forward-looking source of information that explores the present and future trends in the applications of current and emerging wireless communication and network technologies for different healthcare scenaria. It also provides a discovery path on the synergies between the 2.5G and 3G systems and other relevant computing and information technologies and how they prescribe the way for the next generation of m-health services. The book contains 47 chapters, arranged in five thematic sections: Introduction to Mobile M-health Systems, Smart Mobile Applications for Health Professionals, Signal, Image, and Video Compression for M-health Applications, Emergency Health Care Systems and Services, Echography Systems and Services, and Remote and Home Monitoring. This book is intended for all those working in the field of information technologies in biomedicine, as well as for people working in future applications of wireless communications and wireless telemedical systems. It provides different levels of material to researchers, computing engineers, and medical practitioners interested in emerging e-health systems. This book will be a useful reference for all the readers in this important and growing field of research, and will contribute to the roadmap of future m-health systems and improve the development of effective healthcare delivery systems.
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About the author

Jasjit Suri, Ph.D. has spent the last 20 years in the field of computer and electrical engineering, and more than a decade in imaging sciences. Dr. Suri has a masters in computer sciences from the University of Illinois, a doctorate from the University of Washington, Seattle, and will soon receive his EMBA from the Weatherhead School of Management at Case Western Reserve University, Cleveland, Ohio. Dr. Suri has published over 100 technical publications in medical imaging, is a senior member of IEEE, member of the engineering honor societies Eta-Kappa-Nu and Tau-Beta-Phi, and a recipient of the President's Gold Medal in 1980. Prof. Swamy Laxminarayan, D.Sci. championed the field of Biomedical Engineering for over 30 years having held a variety of senior positions within the industry. He is an internationally recognized scientist, engineer, and educator with over 200 technical publications in biomedical information technology, computation biology, signal and image processing, biotechnology, and physiological system modeling. Prof. Laxminarayan is a fellow of AIMBE and a recipient of IEEE 3rd Millennium Medal.

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Additional Information

Publisher
Springer Science & Business Media
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Published on
Jan 4, 2007
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Pages
623
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ISBN
9780387265599
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Language
English
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Genres
Computers / Computer Science
Medical / General
Science / Life Sciences / Biophysics
Technology & Engineering / Biomedical
Technology & Engineering / Engineering (General)
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Content Protection
This content is DRM protected.
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PDE & Level Sets: Algorithmic Approaches to Static & Motion Imagery is specially dedicated to the segmentation of complex shapes from the field of imaging sciences using level sets and PDEs. It covers the fundamentals of level sets, different kinds of concepts of both geodesic curvature flows and planar flows, as well as the power of incorporation of regional-statistics in level set framework. In covering this material, this book presents segmentation of object-in-motion imagery based on level sets in eigen analysis framework, while also presenting classical problems of boundary completion in cognitive images, like the pop-up of subjective contours in the famous triangle of Kanizsa using surface evolution framework, or the mean curvature evolution of a graph with respect to the Riemannian metric induced by the image. All results are presented for modal completion of cognitive objects with missing boundaries.
PDE & Level Sets: Algorithmic Approaches to Static & Motion Imagery is aimed at researchers and educators in imaging sciences, biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry.
Key Features:

-Presents detailed review of PDEs and level sets,
-Covers concepts of geodesic curvature flows and planar flows,
-Offers advance applications of level sets for crack propagation and planar cracks,
-Describes multi-resolution level sets for segmentation of video images,
-Identifies fusion of fuzzy techniques in level set framework,
-Discusses the role of subjective surfaces and Riemannian metric.

MUST WE AGE?
A long life in a healthy, vigorous, youthful body has always been one of humanity's greatest dreams. Recent progress in genetic manipulations and calorie-restricted diets in laboratory animals hold forth the promise that someday science will enable us to exert total control over our own biological aging.
Nearly all scientists who study the biology of aging agree that we will someday be able to substantially slow down the aging process, extending our productive, youthful lives. Dr. Aubrey de Grey is perhaps the most bullish of all such researchers. As has been reported in media outlets ranging from 60 Minutes to The New York Times, Dr. de Grey believes that the key biomedical technology required to eliminate aging-derived debilitation and death entirely—technology that would not only slow but periodically reverse age-related physiological decay, leaving us biologically young into an indefinite future—is now within reach.

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PDE & Level Sets: Algorithmic Approaches to Static & Motion Imagery is specially dedicated to the segmentation of complex shapes from the field of imaging sciences using level sets and PDEs. It covers the fundamentals of level sets, different kinds of concepts of both geodesic curvature flows and planar flows, as well as the power of incorporation of regional-statistics in level set framework. In covering this material, this book presents segmentation of object-in-motion imagery based on level sets in eigen analysis framework, while also presenting classical problems of boundary completion in cognitive images, like the pop-up of subjective contours in the famous triangle of Kanizsa using surface evolution framework, or the mean curvature evolution of a graph with respect to the Riemannian metric induced by the image. All results are presented for modal completion of cognitive objects with missing boundaries.
PDE & Level Sets: Algorithmic Approaches to Static & Motion Imagery is aimed at researchers and educators in imaging sciences, biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry.
Key Features:

-Presents detailed review of PDEs and level sets,
-Covers concepts of geodesic curvature flows and planar flows,
-Offers advance applications of level sets for crack propagation and planar cracks,
-Describes multi-resolution level sets for segmentation of video images,
-Identifies fusion of fuzzy techniques in level set framework,
-Discusses the role of subjective surfaces and Riemannian metric.

It is well-known that speckle is a multiplicative noise that degrades image quality and the visual evaluation in ultrasound imaging. This necessitates the need for robust despeckling techniques for both routine clinical practice and teleconsultation. The goal for this book is to introduce the theoretical background (equations), the algorithmic steps, and the MATLAB code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering and wavelet filtering. The book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts, in the assessment of cardiovascular ultrasound images recorded from the carotid artery. The results of our work presented in this book, suggest that the linear local statistics filter DsFlsmv, gave the best performance, followed by the nonlinear geometric filter DsFgf4d, and the linear homogeneous mask area filter DsFlsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes (of ultrasound images recorded from the carotid artery for the assessment of stroke) based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by two medical experts. A despeckle filtering analysis and evaluation framework is proposed for selecting the most appropriate filter or filters for the images under investigation. These filters can be further developed and evaluated at a larger scale and in clinical practice in the automated image and video segmentation, texture analysis, and classification not only for medical ultrasound but for other modalities as well, such as synthetic aperture radar (SAR) images.
In the usual process of control system design, the assumption is made that the controller is implemented exactly. This assumption is usually reasonable, since clearly, the plant uncertainty is the most significant source of uncertainty in the control system, while controllers are implemented with high-precision hardware. However, inevitably, there will be some amount of uncertainty in the controller, a fact that is largely ignored in existing modern advanced robust control techniques. If the controller is implemented by analogue means, there are some tolerances in the analogue components. More commonly, the controller will be implemented digitally, and consequently there will be uncertainty involved with the quantization in the analogue-digital conversion and rounding in the parameter representation and in the numerical computations. A failure to account for these uncertainties in the controller may result in a controller that is "fragile". A controller is fragile in the sense that very small perturbations in the coefficients of the designed controller destabilize the closed-loop control system.
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- analysis of fragility and finite-precision effects;
- design of optimal controller realizations;
- design of non-fragile robust controllers;
- design of low-complexity digital controllers;
- analysis of quantization effects in fuzzy controllers.
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