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.
