A comprehensive reference of cutting-edge advanced techniques for quantitative image processing and analysis Medical diagnostics and intervention, and biomedical research rely progressively on imaging techniques, namely, the ability to capture, store, analyze, and display images at the organ, tissue, cellular, and molecular level. These tasks are supported by increasingly powerful computer methods to process and analyze images. This text serves as an authoritative resource and self-study guide explaining sophisticated techniques of quantitative image analysis, with a focus on biomedical applications. It offers both theory and practical examples for immediate application of the topics as well as for in-depth study. Advanced Biomedical Image Analysis presents methods in the four major areas of image processing: image enhancement and restoration, image segmentation, image quantification and classification, and image visualization. In each instance, the theory, mathematical foundation, and basic description of an image processing operator is provided, as well as a discussion of performance features, advantages, and limitations. Key algorithms are provided in pseudo-code to help with implementation, and biomedical examples are included in each chapter. Image registration, storage, transport, and compression are also covered, and there is a review of image analysis and visualization software. The accompanying live DVD contains a selection of image analysis software, and it provides most of the algorithms from the book so readers can immediately put their new knowledge to use. Members of the academic community involved in image-related research as well as members of the professional R&D sector will rely on this volume. It is also well suited as a textbook for graduate-level image processing classes in the computer science and engineering fields.
This book provides an essential understanding of statistical concepts necessary for the analysis of genomic and proteomic data using computational techniques. The author presents both basic and advanced topics, focusing on those that are relevant to the computational analysis of large data sets in biology. Chapters begin with a description of a statistical concept and a current example from biomedical research, followed by more detailed presentation, discussion of limitations, and problems. The book starts with an introduction to probability and statistics for genome-wide data, and moves into topics such as clustering, classification, multi-dimensional visualization, experimental design, statistical resampling, and statistical network analysis. Clearly explains the use of bioinformatics tools in life sciences research without requiring an advanced background in math/statistics Enables biomedical and life sciences researchers to successfully evaluate the validity of their results and make inferences Enables statistical and quantitative researchers to rapidly learn novel statistical concepts and techniques appropriate for large biological data analysis Carefully revisits frequently used statistical approaches and highlights their limitations in large biological data analysis Offers programming examples and datasets Includes chapter problem sets, a glossary, a list of statistical notations, and appendices with references to background mathematical and technical material Features supplementary materials, including datasets, links, and a statistical package available online Statistical Bioinformatics is an ideal textbook for students in medicine, life sciences, and bioengineering, aimed at researchers who utilize computational tools for the analysis of genomic, proteomic, and many other emerging high-throughput molecular data. It may also serve as a rapid introduction to the bioinformatics science for statistical and computational students and audiences who have not experienced such analysis tasks before.
This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.
A must-have compendium on biomedical telemetry for all biomedical professional engineers, researchers, and graduate students in the field Handbook of Biomedical Telemetry describes the main components of a typical biomedical telemetry system, as well as its technical challenges. Written by a diverse group of experts in the field, it is filled with overviews, highly-detailed scientific analyses, and example applications of biomedical telemetry. The book also addresses technologies for biomedical sensing and design of biomedical telemetry devices with special emphasis on powering/integration issues and materials for biomedical telemetry applications. Handbook of Biomedical Telemetry: Describes the main components of a typical biomedical telemetry system, along with the technical challenges Discusses issues of spectrum regulations, standards, and interoperability—while major technical challenges related to advanced materials, miniaturization, and biocompatibility issues are also included Covers body area electromagnetics, inductive coupling, antennas for biomedical telemetry, intra-body communications, non-RF communication links for biomedical telemetry (optical biotelemetry), as well as safety issues, human phantoms, and exposure assessment to high-frequency biotelemetry fields Presents biosensor network topologies and standards; context-aware sensing and multi-sensor fusion; security and privacy issues in biomedical telemetry; and the connection between biomedical telemetry and telemedicine Introduces clinical applications of Body Sensor Networks (BSNs) in addition to selected examples of wearable, implantable, ingestible devices, stimulator and integrated mobile healthcare system paradigms for monitoring and therapeutic intervention Covering biomedical telemetry devices, biosensor network topologies and standards, clinical applications, wearable and implantable devices, and the effects on the mobile healthcare system, this compendium is a must-have for professional engineers, researchers, and graduate students.
Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience.
Multiresolution analysis using the wavelet transform has received considerable attention in recent years by researchers in various fields. It is a powerful tool for efficiently representing signals and images at multiple levels of detail with many inherent advantages, including compression, level-of-detail display, progressive transmission, level-of-detail editing, filtering, modeling, fractals and multifractals, etc. This book aims to provide a simple formalization and new clarity on multiresolution analysis, rendering accessible obscure techniques, and merging, unifying or completing the technique with encoding, feature extraction, compressive sensing, multifractal analysis and texture analysis. It is aimed at industrial engineers, medical researchers, university lab attendants, lecturer-researchers and researchers from various specializations. It is also intended to contribute to the studies of graduate students in engineering, particularly in the fields of medical imaging, intelligent instrumentation, telecommunications, and signal and image processing. Given the diversity of the problems posed and addressed, this book paves the way for the development of new research themes, such as brain–computer interface (BCI), compressive sensing, functional magnetic resonance imaging (fMRI), tissue characterization (bones, skin, etc.) and the analysis of complex phenomena in general. Throughout the chapters, informative illustrations assist the uninitiated reader in better conceptualizing certain concepts, taking the form of numerous figures and recent applications in biomedical engineering, communication, multimedia, finance, etc.
This book presents and describes imaging technologies that can be used to study chemical processes and structural interactions in dynamic systems, principally in biomedical systems. The imaging technologies, largely biomedical imaging technologies such as MRT, Fluorescence mapping, raman mapping, nanoESCA, and CARS microscopy, have been selected according to their application range and to the chemical information content of their data. These technologies allow for the analysis and evaluation of delicate biological samples, which must not be disturbed during the profess. Ultimately, this may mean fewer animal lab tests and clinical trials.
The ideal reference to Canon's EOS 5D Mark III for professionals and serious hobbyists The Canon EOS 5D Mark III offers professional photographers and advanced amateurs a wide range of top-flight dSLR capabilities. Canon users love For Dummies guides, with more than 100,000 copies of previous Canon camera guides sold. Like its predecessors, this one is packed with colorful examples that illustrate camera features and inspire you to capture your own super images. It explains the camera controls and menus, shows you how to take full advantage of all the features, discusses output options and image editing, and much more. Geared to the needs of professional dSLR photographers and serious hobbyists, this guide covers all the features of the Canon EOS 5D Mark III Explores the camera body, menu screen, auto settings, and image settings Shows how to use the video modes, priority settings, manual settings, and focus modes to capture the best images Provides suggestions and inspiration with more than 300 full-color photos Covers image editing and output options Features tips, techniques, and projects to help you get the most from your camera's capabilities Canon EOS 5D Mark III For Dummies is the perfect partner for your new dSLR.
This fourth and full colour edition updates and expands a widely-used textbook aimed at advanced undergraduate and postgraduate students taking courses in remote sensing and GIS in Geography, Geology and Earth/Environmental Science departments. Existing material has been brought up to date and new material has been added. In particular, a new chapter, exploring the two-way links between remote sensing and environmental GIS, has been added. New and updated material includes: A website at www.wiley.com/go/mather4 that provides access to an updated and expanded version of the MIPS image processing software for Microsoft Windows, PowerPoint slideshows of the figures from each chapter, and case studies, including full data sets, Includes new chapter on Remote Sensing and Environmental GIS that provides insights into the ways in which remotely-sensed data can be used synergistically with other spatial data sets, including hydrogeological and archaeological applications, New section on image processing from a computer science perspective presented in a non-technical way, including some remarks on statistics, New material on image transforms, including the analysis of temporal change and data fusion techniques, New material on image classification including decision trees, support vector machines and independent components analysis, and Now in full colour throughout. This book provides the material required for a single semester course in Environmental Remote Sensing plus additional, more advanced, reading for students specialising in some aspect of the subject. It is written largely in non-technical language yet it provides insights into more advanced topics that some may consider too difficult for a non-mathematician to understand. The case studies available from the website are fully-documented research projects complete with original data sets. For readers who do not have access to commercial image processing software, MIPS provides a licence-free, intuitive and comprehensive alternative.
Digital Spectral Analysis provides a single source that offers complete coverage of the spectral analysis domain. This self-contained work includes details on advanced topics that are usually presented in scattered sources throughout the literature. The theoretical principles necessary for the understanding of spectral analysis are discussed in the first four chapters: fundamentals, digital signal processing, estimation in spectral analysis, and time-series models. An entire chapter is devoted to the non-parametric methods most widely used in industry. High resolution methods are detailed in a further four chapters: spectral analysis by stationary time series modeling, minimum variance, and subspace-based estimators. Finally, advanced concepts are the core of the last four chapters: spectral analysis of non-stationary random signals, space time adaptive processing: irregularly sampled data processing, particle filtering and tracking of varying sinusoids. Suitable for students, engineers working in industry, and academics at any level, this book provides a rare complete overview of the spectral analysis domain.