Main description:

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.

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