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Guide to Medical Image Analysis

Methods and Algorithms

  • Textbook
  • © 2012

Overview

  • An in-depth-introduction into medical image analysis, suitable for use as a textbook
  • Provides a detailed discussion on segmentation, classification and registration techniques
  • Presents the methods in the context of their adequate use, based on the constraints necessary for successful application
  • Includes supplementary material: sn.pub/extras

Part of the book series: Advances in Computer Vision and Pattern Recognition (ACVPR)

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About this book

This book presents a comprehensive overview of medical image analysis. Practical in approach, the text is uniquely structured by potential applications. Features: presents learning objectives, exercises and concluding remarks in each chapter, in addition to a glossary of abbreviations; describes a range of common imaging techniques, reconstruction techniques and image artefacts; discusses the archival and transfer of images, including the HL7 and DICOM standards; presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing; examines various feature detection and segmentation techniques, together with methods for computing a registration or normalisation transformation; explores object detection, as well as classification based on segment attributes such as shape and appearance; reviews the validation of an analysis method; includes appendices on Markov random field optimization, variational calculus and principal component analysis.

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Keywords

Table of contents (14 chapters)

Authors and Affiliations

  • Computer Science Department, ISG, Otto-von-Guericke-Universität Magdeburg, Magdeburg, Germany

    Klaus D. Toennies

About the author

Dr. Klaus D. Toennies is a Professor of Image Processing and Pattern Recognition at the Department of Simulation and Graphics of the Otto-von-Guericke University of Magdeburg, Germany.

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