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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.
List of contents
The Analysis of Medical Images.- Digital Image Acquisition.- Image Storage and Transfer.- Image Enhancement.- Feature Detection.- Segmentation: Principles and Basic Techniques.- Segmentation in Feature Space.- Segmentation as a Graph Problem.- Active Contours and Active Surfaces.- Registration and Normalization.- Shape, Appearance and Spatial Relationships.- Classification and Clustering.- Validation.- Appendix.
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.
Summary
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.
Additional text
“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)
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"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)
