Guide to Medical Image Analysis: Methods and Algorithms

✍ Scribed by Klaus D. Toennies (auth.)

• Publisher: Springer-Verlag London
• Year: 2017
• Tongue: English
• Leaves: 609
• Series: Advances in Computer Vision and Pattern Recognition
• Edition: 2
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xxiv
The Analysis of Medical Images....Pages 1-22
Digital Image Acquisition....Pages 23-94
Image Storage and Transfer....Pages 95-123
Image Enhancement....Pages 125-172
Feature Detection....Pages 173-207
Segmentation: Principles and Basic Techniques....Pages 209-247
Segmentation in Feature Space....Pages 249-273
Segmentation as a Graph Problem....Pages 275-310
Active Contours and Active Surfaces....Pages 311-360
Registration and Normalization....Pages 361-404
Shape, Appearance and Spatial Relationships....Pages 405-472
Classification and Clustering....Pages 473-528
Validation....Pages 529-562
Appendix....Pages 563-578
Erratum to: Guide to Medical Image Analysis....Pages E1-E1
Back Matter....Pages 579-589

✦ Subjects

Image Processing and Computer Vision;Imaging / Radiology