Guide to Medical Image Analysis : Methods and Algorithms / by Klaus D. Toennies.

Format:

Book

Author/Creator:

Toennies, Klaus D., author.

Contributor:

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Advances in computer vision and pattern recognition 2191-6586

Advances in Computer Vision and Pattern Recognition, 2191-6586

Language:

English

Subjects (All):

Optical data processing.

Radiology.

Image Processing and Computer Vision.

Imaging / Radiology.

Local Subjects:

Image Processing and Computer Vision.

Imaging / Radiology.

Physical Description:

1 online resource (XXIV, 589 pages) : 384 illustrations, 197 illustrations in color.

Edition:

Second edition 2017.

Contained In:

Springer eBooks

Place of Publication:

London : Springer London : Imprint: Springer, 2017.

System Details:

text file PDF

Summary:

This comprehensive guide provides a uniquely practical, application-focused introduction to medical image analysis. The text presents a concise examination of each of the key concepts, enabling the reader to understand the interdependencies between them before delving deeper into the derivations and technical details. 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, in addition to a glossary of abbreviations 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 (NEW) Examines analysis methods in view of image-based guidance in the operating room, designed to aid the operator in adapting their intervention during an operation (NEW) Discusses the use of deep convolutional networks for segmentation and labeling tasks, describing how this network architecture differs from multi-layer perceptrons (NEW) Includes appendices on Markov random field optimization, variational calculus and principal component analysis This clearly-written guide/reference serves as a classroom-tested textbook for courses on medical image processing and analysis, with suggestions for course outlines supplied in the preface. Professionals in medical imaging technology, as well as computer scientists and electrical engineers specializing in medical applications, will also find the book an ideal resource for self-study.

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.

Other Format:

Printed edition:

ISBN:

978-1-4471-7320-5

9781447173205

Access Restriction:

Restricted for use by site license.