Intensity-Based Registration for Lung Motion Estimation

Kunlin Cao; Kai Ding; Ryan E Amelon; Kaifang Du; Joseph M Reinhardt; Madhavan L Raghavan; Gary E Christensen

doi:10.1007/978-3-642-36441-9_7

Back

Intensity-Based Registration for Lung Motion Estimation

Book chapter

Open access

Intensity-Based Registration for Lung Motion Estimation

Kunlin Cao, Kai Ding, Ryan E Amelon, Kaifang Du, Joseph M Reinhardt, Madhavan L Raghavan and Gary E Christensen

4D Modeling and Estimation of Respiratory Motion for Radiation Therapy, pp.125-158

Biological and Medical Physics, Biomedical Engineering, Springer Berlin Heidelberg

05/31/2013

DOI: 10.1007/978-3-642-36441-9_7

Files and links (1)

url

https://doi.org/10.1007/978-3-642-36441-9_7View

Published (Version of record) Open Access

Abstract

Image registration plays an important role within pulmonary image analysis. The task of registration is to find the spatial mapping that brings two images into alignment. Registration algorithms designed for matching 4D lung scans or two 3D scans acquired at different inflation levels can catch the temporal changes in position and shape of the region of interest. Accurate registration is critical to post-analysis of lung mechanics and motion estimation. In this chapter, we discuss lung-specific adaptations of intensity-based registration methods for 3D/4D lung images and review approaches for assessing registration accuracy. Then we introduce methods for estimating tissue motion and studying lung mechanics. Finally, we discuss methods for assessing and quantifying specific volume change, specific ventilation, strain/ stretch information and lobar sliding.

Image Registration

Registration Algorithm

Maximal Principal Strain

Registration Method

Registration Accuracy

Details

Title: Subtitle: Intensity-Based Registration for Lung Motion Estimation
Creators: Kunlin Cao - Biomedical Image Analysis Laboratory, GE Global Research Center, Niskayuna, USA
Kai Ding - Department of Biomedical Engineering, The University of Iowa, Iowa City, USA
Ryan E Amelon - Department of Biomedical Engineering, The University of Iowa, Iowa City, USA
Kaifang Du - Department of Biomedical Engineering, The University of Iowa, Iowa City, USA
Joseph M Reinhardt - Department of Biomedical Engineering, The University of Iowa, Iowa City, USA
Madhavan L Raghavan - Department of Biomedical Engineering, The University of Iowa, Iowa City, USA
Gary E Christensen - Department of Electrical and Computer, The University of Iowa, Iowa City, USA
Resource Type: Book chapter
Publication Details: 4D Modeling and Estimation of Respiratory Motion for Radiation Therapy, pp.125-158
Series: Biological and Medical Physics, Biomedical Engineering
DOI: 10.1007/978-3-642-36441-9_7
ISSN: 1618-7210
Publisher: Springer Berlin Heidelberg; Berlin, Heidelberg
Language: English
Date published: 05/31/2013
Academic Unit: Roy J. Carver Department of Biomedical Engineering; Radiology; Electrical and Computer Engineering; Radiation Oncology; Radiation Research Laboratory
Record Identifier: 9984064235502771

Metrics

65 Record Views