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Advanced Biomedical Image Analysis

Posted on 2012-06-18




Name:Advanced Biomedical Image Analysis
ASIN/ISBN:0470624582
Language: English
Publish Date: 2010
ISBN: 0470624582
Pages: 528 pages
File Type: PDF
File Size: 5,5 MB
   Advanced Biomedical Image Analysis

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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.

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.



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