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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.
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.- Detection and Segmentation by Shape and Appearance.- Classification and Clustering.- Validation.- Optimisation of Markov Random Fields.- Variational Calculus.- Principal Component Analysis.- References.
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 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.
