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-xxiv
  2. Klaus D. Toennies
    Pages 1-22
  3. Klaus D. Toennies
    Pages 23-94
  4. Klaus D. Toennies
    Pages 95-123
  5. Klaus D. Toennies
    Pages 125-172
  6. Klaus D. Toennies
    Pages 173-207
  7. Klaus D. Toennies
    Pages 209-247
  8. Klaus D. Toennies
    Pages 249-273
  9. Klaus D. Toennies
    Pages 275-310
  10. Klaus D. Toennies
    Pages 311-360
  11. Klaus D. Toennies
    Pages 361-404
  12. Klaus D. Toennies
    Pages 405-472
  13. Klaus D. Toennies
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  14. Klaus D. Toennies
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  15. Klaus D. Toennies
    Pages 563-578
  16. Klaus D. Toennies
    Pages E1-E1
  17. Back Matter
    Pages 579-589

About this book

Introduction

This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. The text presents a concise examination of each of the key concepts, enabling the reader to understand the interdependencies between them before delving deeper into the derivations and technical details. This fully updated new edition has been enhanced with material on the latest developments in the field, whilst retaining the original focus on segmentation, classification and registration.

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 artifacts, and discusses the archival and transfer of images
  • Reviews an expanded selection of techniques for image enhancement, feature detection, feature generation, segmentation, registration, and validation (NEW)
  • Examines analysis methods in view of image-based guidance in the operating room, designed to aid the operator in adapting their intervention during an operation (NEW)
  • Discusses the use of deep convolutional networks for segmentation and labeling tasks, describing how this network architecture differs from multi-layer perceptrons (NEW)
  • Includes appendices on Markov random field optimization, variational calculus and principal component analysis

This clearly-written guide/reference serves as a classroom-tested textbook for courses on medical image processing and analysis, with suggestions for course outlines supplied in the preface. Professionals in medical imaging technology, as well as computer scientists and electrical engineers specializing in medical applications, will also find the book an ideal resource for self-study.

Keywords

Classification Image Processing Medical Image Analysis Object Detection Registration Segmentation

Authors and affiliations

  • Klaus D. Toennies
    • 1
  1. 1.Otto-von-Guericke-Universität Magdeburg Computer Science Department, ISGMagdeburgGermany

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4471-7320-5
  • Copyright Information Springer-Verlag London Ltd. 2017
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-4471-7318-2
  • Online ISBN 978-1-4471-7320-5
  • Series Print ISSN 2191-6586
  • Series Online ISSN 2191-6594
  • About this book