Paper
12 May 2004 Comparison of different follow-up lung registration methods with and without segmentation
Author Affiliations +
Abstract
In modern multi slice CT scanners the increasing amount of data also increases the demand on image processing methods that assist the diagnosis. For the detection and classification of lung nodules in a follow up study it is very helpful to have the slices of a previous scan aligned with the slices of the current scan. This is a typical problem of image registration, for which different types of solutions exist. We investigated the accuracy and computation times of a rigid body, an affine, and a spline based elastic registration approach on the complete data set, and compared the results to a method where the registration was preceded by a segmentation of the lung volume. The registration quality was determined on a ground truth of previously determined lung nodule locations by measuring the average distance of corresponding nodules. It was found that an affine registration is slightly better than a rigid body registration, and that both are much faster than the elastic registration, which in turn showed the best registration quality. A good compromise was the affine registration on a previously segmented lung volume, which in total is not much slower than the registration without segmentation, but shows better alignment and higher robustness.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Blaffert and Rafael Wiemker "Comparison of different follow-up lung registration methods with and without segmentation", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.535345
Lens.org Logo
CITATIONS
Cited by 21 scholarly publications and 5 patents.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Lung

Image registration

Image segmentation

Computed tomography

Tissues

Distance measurement

Computer aided diagnosis and therapy

Back to Top