Logo - springer
Slogan - springer

Springer Vieweg - IT & Informatik - Grundlagen | Registration Methods for Pulmonary Image Analysis - Integration of Morphological and Physiological

Registration Methods for Pulmonary Image Analysis

Integration of Morphological and Physiological Knowledge

Schmidt-Richberg, Alexander

2014, XVI, 168 p. 48 illus., 14 illus. in color.

Available Formats:

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.


(net) price for USA

ISBN 978-3-658-01662-3

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase

learn more about Springer eBooks

add to marked items


Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-3-658-01661-6

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days

add to marked items

  • ​Publication in the field of natural sciences​

Various applications in the field of pulmonary image analysis require a registration of CT images of the lung. For example, a registration-based estimation of the breathing motion is employed to increase the accuracy of dose distribution in radiotherapy. Alexander Schmidt-Richberg develops methods to explicitly model morphological and physiological knowledge about respiration in algorithms for the registration of thoracic CT images. The author focusses on two lung-specific issues: on the one hand, the alignment of the interlobular fissures and on the other hand, the estimation of sliding motion at the lung boundaries. He shows that by explicitly considering these aspects based on a segmentation of the respective structure, registration accuracy can be significantly improved.



·         Registration

·         Segmentation

·         Level Set Segmentation

·         Motion Estimation

·         Sliding Motion

·         Integrated Registration and Segmentation


Target Groups

·         Researchers and students of medical informatics, medical imaging

·         Radiologists, physicians



The Author

Alexander Schmidt-Richberg works as a research scientist with a focus on image registration and segmentation. He received his PhD at the Institute of Medical Informatics, University of Lübeck, Germany, in 2013. Currently, he is a member of the Biomedical Image Analysis Group, Imperial College London, UK.



The series Aktuelle Forschung Medizintechnik is edited by Thorsten Buzug.

Content Level » Research

Keywords » Image Fusion - Medical Imaging - Motion Estimation - Pulmonary Image Analysis - Registration - Segmentation

Related subjects » Grundlagen

Table of contents / Preface / Sample pages 

Popular Content within this publication 



Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Computer Science (general).