Academic Press Medical Image Analysis (The MICCAI Society book Series)

Medical imaging is increasingly at the base of many fundamental breakthroughs in biomedical sciences, becoming a fundamental enabling technology of biomedical scientific progress. This book presents practical knowledge on medical image computing and analysis Written by top educators and experts in the field, this text is a modern, practical, broad, and self-contained reference that conveys a mix of fundamental methodological concepts within different medical domains, reflecting the nature of the discipline today. Learn: The core representations and properties of digital images and image enhancement techniquesAdvanced image computing methods including segmentation, registration, motion and shape analysis, and machine learningHow medical image computing (MIC) is used in clinical and medical researchHow to identify alternative strategies and employ software tools to solve typical problems in MIC An authoritative description of key concepts and methods Tutorial-based sections that clearly explain the principles and their application to different medical domains Self-contained chapters provide flexibility, allowing the text to be used on courses with different structures A representative selection of topics to match a modern and relevant approach to medical image computing Focus on medical image computing as a technology to meet clinical needs Review Gives graduates and researchers an understanding of medical image analysis methods and their applications About the Author Alejandro (Alex) Frangi is Professor of Biomedical Image Computing at the University of Sheffield (USFD) and affiliated to the Electronic & Electrical Engineering Department. He is also Director of the Center for Computational Imaging and Simulation Technologies in Biomedicine and member of INSIGNEO Institute for in silico Medicine. Prof Frangi is Fellow of IEEE. His main research interests are in medical image computing, medical imaging and image-based computational physiology. Prof. Frangi has edited a book, published 5 editorial articles and over 90 journal papers in key international journals of his research field, as well as more than 120 book chapters and international conference papers. He has twice been Guest Editor of special issues of IEEE Trans on Medical Imaging, one on IEEE Trans Biomed Eng, and one of Medical Image Analysis journal. Jerry L. Prince has research interests in image processing and computer vision with primary application to medical imaging. He has studied and developed methods for imaging motion in the heart, tongue, and brain using magnetic resonance imaging. He has applied both statistical estimation and computer vision methods to the analysis of brain structure with applications in normal aging, Alzheimer’s disease, and multiple sclerosis. He is also co founder of Diagnosoft, Inc., a medical imaging software company. He received the BS degree from the University of Connecticut in 1979 and the S.M., E.E., and PhD degrees in 1982, 1986, and 1988, respectively, from the Massachusetts Institute of Technology, all in electrical engineering and computer science. Dr. Milan Sonka, Ph.D., is the Co-Founder of VIDA Diagnostics, Inc. Dr. Sonka has been a Professor of Electrical and Computer Engineering at University of Iowa since 2000, Ophthalmology and Visual Sciences since 2006, Applied Mathematical and Computational Sciences since 2001 and Radiation Oncology since 2006. He also serves as Co-director of Iowa Institute for Biomedical Imaging at the University of Iowa. He served as an Assistant Professor at Department of Control Engineering, Czech Technical University of Prague from 1984 to 1990. He served as Visiting Assistant Professor at Department of Electrical and Computer Engineering, The University of Iowa from 1990 to 1993. He served as Visiting Associate Professor from 1993 to 1994 and Associate Professor from 1994 to 2000. Dr. Sonka is a well-known scholar in the area of qu