Guide to Medical Image Analysis

1. Front Matter

   Pages i-xxiv

   PDF

2. The Analysis of Medical Images

   • Klaus D. Toennies

   Pages 1-22

3. Digital Image Acquisition

   • Klaus D. Toennies

   Pages 23-94

4. Image Storage and Transfer

   • Klaus D. Toennies

   Pages 95-123

5. Image Enhancement

   • Klaus D. Toennies

   Pages 125-172

6. Feature Detection

   • Klaus D. Toennies

   Pages 173-207

7. Segmentation: Principles and Basic Techniques

   • Klaus D. Toennies

   Pages 209-247

8. Segmentation in Feature Space

   • Klaus D. Toennies

   Pages 249-273

9. Segmentation as a Graph Problem

   • Klaus D. Toennies

   Pages 275-310

10. Active Contours and Active Surfaces

    • Klaus D. Toennies

    Pages 311-360

11. Registration and Normalization

    • Klaus D. Toennies

    Pages 361-404

12. Shape, Appearance and Spatial Relationships

    • Klaus D. Toennies

    Pages 405-472

13. Classification and Clustering

    • Klaus D. Toennies

    Pages 473-528

14. Validation

    • Klaus D. Toennies

    Pages 529-562

15. Appendix

    • Klaus D. Toennies

    Pages 563-578

16. Erratum to: Guide to Medical Image Analysis

    • Klaus D. Toennies

    Pages E1-E1

17. Back Matter

    Pages 579-589

    PDF

This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. 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; 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; examines analysis methods in view of image-based guidance in the operating room (NEW); discusses the use of deep convolutional networks for segmentation and labeling tasks (NEW); includes appendices on Markov random field optimization, variational calculus and principal component analysis.

• Classification
• Image Processing
• Medical Image Analysis
• Object Detection
• Registration
• Segmentation

“I am glad to have had the opportunity to review this book, which is suitable for beginners to learn the overall, big picture of medical image analysis. … the book is very well written with details of the algorithms being described in a way that pupils can easily understand. The exercises and references are reasonable and helpful … .” (Guang Yang, International Association of Pattern Recognition Newsletter, Vol. 40 (1), January, 2018)



“The book is well written and accurate. The author states that he has made a number of additions and corrections in this new edition; the result is very good. … it’s well suited as a textbook for medical professionals. I am evaluating it for adoption in a medical imaging course, and would recommend it to those in the medical field who want a detailed discussion of medical image analysis.” (Computing Reviews, October, 2017)

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

  Klaus D. Toennies

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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