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Guide to Medical Image Analysis

Methods and Algorithms

  • Klaus D. Toennies

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

Table of contents

  1. Front Matter
    Pages I-XX
  2. Klaus D. Toennies
    Pages 1-19
  3. Klaus D. Toennies
    Pages 21-82
  4. Klaus D. Toennies
    Pages 83-109
  5. Klaus D. Toennies
    Pages 111-146
  6. Klaus D. Toennies
    Pages 147-169
  7. Klaus D. Toennies
    Pages 171-209
  8. Klaus D. Toennies
    Pages 211-233
  9. Klaus D. Toennies
    Pages 235-259
  10. Klaus D. Toennies
    Pages 261-297
  11. Klaus D. Toennies
    Pages 299-331
  12. Klaus D. Toennies
    Pages 333-378
  13. Klaus D. Toennies
    Pages 379-412
  14. Klaus D. Toennies
    Pages 413-442
  15. Klaus D. Toennies
    Pages 443-457
  16. Back Matter
    Pages 459-468

About this book

Introduction

Analysis of medical imaging poses special challenges distinct from traditional image analysis. Furthermore, the analysis must fit into the clinical workflow within which it has been requested.

This important guide/reference presents a comprehensive overview of medical image analysis. Highly practical in its approach, the text is uniquely structured by potential applications, supported by exercises throughout. Each of the key concepts are introduced in a concise manner, allowing the reader to understand the interdependencies between them before exploring the deeper details and derivations.

Topics and 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

This easy-to-follow, classroom-tested textbook is ideal for undergraduate and graduate courses on medical image analysis and related subjects – with possible course outlines suggested in the Preface. The work can also be used as a self-study guide for professionals in medical imaging technology, and for computer scientists and engineers wishing to specialise in medical applications. 

Keywords

Classification Image Processing Medical Image Analysis Object Detection Registration Segmentation

Authors and affiliations

  • Klaus D. Toennies
    • 1
  1. 1.Computer Science Department, ISGOtto-von-Guericke-Universität MagdeburgMagdeburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-2751-2
  • Copyright Information Springer-Verlag London Limited 2012
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-2750-5
  • Online ISBN 978-1-4471-2751-2
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • Buy this book on publisher's site
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