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The book is designed for end users in the field of digital imaging, who wish to update their skills and understanding with the latest techniques in image analysis. The book emphasizes the conceptual framework of image analysis and the effective use of image processing tools. It uses applications in a variety of fields to demonstrate and consolidate both specific and general concepts, and to build intuition, insight and understanding. Although the chapters are essentially self-contained they reference other chapters to form an integrated whole. Each chapter employs a pedagogical approach to ensure conceptual learning before introducing specific techniques and “tricks of the trade”. The book concentrates on a number of current research applications, and will present a detailed approach to each while emphasizing the applicability of techniques to other problems. The field of topics is wide, ranging from compressive (non-uniform) sampling in MRI, through automated retinal vessel analysis to 3-D ultrasound imaging and more. The book is amply illustrated with figures and applicable medical images. The reader will learn the techniques which experts in the field are currently employing and testing to solve particular research problems, and how they may be applied to other problems.
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Geoff Dougherty is Professor of Applied Physics and Medical Imaging at California State University Channel Islands, where he teaches both undergraduate and graduate courses in image analysis, pattern recognition and medical imaging. He has been conducting research in the applications of image processing and analysis to medical images for over 20 years. In 2009 he was awarded a Fulbright Senior Scholarship to undertake research in Brisbane, Australia. He has published numerous articles in international journals, and is the author of several book chapters and a textbook in image analysis. He is a Fellow of the IET, a Senior Member of the IEEE and a Member of the American Association of Physicists in Medicine (AAPM), and has held positions at Kuwait University, Keele University, Monash University, the Science University of Malaysia (USM) and the Swiss Federal Institute of Technology (ETH).
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