Swamy Laxminarayan – författare

In the medical field, medical imagery has become a discipline of its own, given the nature of its applications in the understanding of the human body and medical diagnostics. Image processing techniques are the core tools for solving these biomedical problems. The applications of level sets has made a significant impact on medical imagery primarily because of its ability to perform efficient topology preservation and fast shape recovery. This has dominated the binary, grayscale and colour frameworks, which the eye can perceive. It has not only the ability to find boundaries and surfaces that are deep seated in 2-D and 3-D volumes respectively, but also provide satisfactory solutions for the completion of cognitive objects with missing boundaries.

Handbook of Biomedical Image Analysis: Segmentation Models (Volume I) is dedicated to the segmentation of complex shapes from the field of imaging sciences using different mathematical techniques. This volume is aimed at researchers and educators in imaging sciences, radiological imaging, clinical and diagnostic imaging, physicists covering different medical imaging modalities, as well as researchers in biomedical engineering, applied mathematics, algorithmic development, computer vision, signal processing, computer graphics and multimedia in general, both in academia and industry .Key Features:- Principles of intra-vascular ultrasound (IVUS)- Principles of positron emission tomography (PET)- Physical principles of magnetic resonance angiography (MRA).- Basic and advanced level set methods- Shape for shading method for medical image analysis- Wavelet transforms and other multi-scale analysis functions- Three dimensional deformable surfaces- Level Set application for CT lungs, brain MRI and MRA volume segmentation- Segmentation of incomplete tomographic medical data sets- Subjective level sets for missing boundaries for segmentation

With rapid advancements in technology, body imaging or components thereof, have become ubiquitous in medicine. While the biomedical devices such as the MRI, CT, X-rays, Ultrasound, PET/SPECT and Microscopy etc, provide us with high resolution images, the challenges that have continued to confront us with, lie in the interpretation of the vast amounts of data generated by these devices. Biomedical applications are the 'bottom-line' essentials in the diagnostic world. It is this diagnostic interpretation feature that forms the core niche for these books and will serve the needs of a broad spectrum of audience including researchers, research clinicians, and students. Together the three volumes will illustrate the role of the fusion of registration and segmentation systems for complete biomedical applications therapy delivery benefiting the biomedical doctors, clinical researchers, radiologists and others.

With rapid advancements in technology, body imaging or components thereof, have become ubiquitous in medicine. While the biomedical devices such as the MRI, CT, X-rays, Ultrasound, PET/SPECT and Microscopy etc, provide us with high resolution images, the challenges that have continued to confront us with, lie in the interpretation of the vast amounts of data generated by these devices. Biomedical applications are the ‘bottom-line’ essentials in the diagnostic world. It is this diagnostic interpretation feature that forms the core niche for these books and will serve the needs of a broad spectrum of audience including researchers, research clinicians, and students. Together these three volumes of the Handbook of Biomedical Image Analysis, Volume 1 - Segementation Part A; Volume 2-Segmentation Part B; and Volume 3 - Registration, illustrate the role of the fusion of registration and segmentation systems for complete biomedical applications therapy delivery benefiting the biomedical doctors, clinical researchers, radiologists and others. Each volume in this set features a CD-ROM containing pedagogical material and numerous color illustrations.

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.

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.

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.