Guide to Medical Image Analysis : Methods and Algorithms

Klaus D. Toennies

ISBN 10: 144717318X / ISBN 13: 9781447173182

Published by Springer, Springer, 2017

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9781447173182

Bibliographic Details

• Title: Guide to Medical Image Analysis : Methods and Algorithms
• Publisher: Springer, Springer
• Publication Date: 2017
• Language: English
• ISBN 10: 144717318X
• ISBN 13: 9781447173182
• Binding: Buch
• Edition: 2nd Edition
• Condition: Neu
• Dimensions: 241W x 160H x 37D millimeters 241 millimeters width by 160 millimeters height by 37 millimeters depth
• Weight: 1192 grams

About this title

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.

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.