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Medical Image Analysis, 2nd Edition
ISBN: 978-0-470-92289-7
March 2011
Wiley-IEEE Press
400 pages
Now updated—the most comprehensive reference of medical imaging modalities and image analysis techniques
The last two decades have witnessed revolutionary advances in medical imaging and computerized medical image processing. With the advent and enhancement of numerous sophisticated medical imaging modalities, intelligent processing of multi-dimensional images has become critical in radiological and diagnostic applications.
This benchmark text takes a unique, all-inclusive approach to the topic—one that weaves together medical physics, medical imaging instrumentation, and advanced image analysis methods. This Second Edition is completely revised and expanded to provide a broader foundation, helping engineers, medical professionals, and students alike understand medical imaging principles, perform intelligent image interpretation, and navigate the intricacies of instrumentation, data collection, image reconstruction, and computerized image analysis for radiological computer-aided evaluation and diagnosis. New chapters cover:
This updated edition presents individual chapters focused on x-ray, MRI, nuclear medicine, and ultrasound imaging modalities with additional details and recent advances. In addition, chapters on image reconstructions and visualizations have been significantly enhanced to include, respectively, 3-D statistical estimation–based reconstruction methods, feature classification and multi-modality image visualization. Examples with clinical images for medical image analysis and computer-aided diagnosis are provided throughout, as well as skill-building MATLAB® exercises.
An ideal learning tool, this state-of-the-art resource can be used for one- or two-semester based senior undergraduate and/or graduate-level courses. Students in medical imaging and image processing, electrical and computer engineering, computer science, and biomedical engineering as well as physicians, medical physicists, and researchers will gain the knowledge to master the complexities of today's radiological and diagnostic applications.