Paper
12 March 2010 Evaluation of five non-rigid image registration algorithms using the NIREP framework
Ying Wei, Gary E. Christensen, Joo Hyun Song, David Rudrauf, Joel Bruss, Jon G. Kuhl, Thomas J. Grabowski
Author Affiliations +
Abstract
Evaluating non-rigid image registration algorithm performance is a difficult problem since there is rarely a "gold standard" (i.e., known) correspondence between two images. This paper reports the analysis and comparison of five non-rigid image registration algorithms using the Non-Rigid Image Registration Evaluation Project (NIREP) (www.nirep.org) framework. The NIREP framework evaluates registration performance using centralized databases of well-characterized images and standard evaluation statistics (methods) which are implemented in a software package. The performance of five non-rigid registration algorithms (Affine, AIR, Demons, SLE and SICLE) was evaluated using 22 images from two NIREP neuroanatomical evaluation databases. Six evaluation statistics (relative overlap, intensity variance, normalized ROI overlap, alignment of calcarine sulci, inverse consistency error and transitivity error) were used to evaluate and compare image registration performance. The results indicate that the Demons registration algorithm produced the best registration results with respect to the relative overlap statistic but produced nearly the worst registration results with respect to the inverse consistency statistic. The fact that one registration algorithm produced the best result for one criterion and nearly the worst for another illustrates the need to use multiple evaluation statistics to fully assess performance.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ying Wei, Gary E. Christensen, Joo Hyun Song, David Rudrauf, Joel Bruss, Jon G. Kuhl, and Thomas J. Grabowski "Evaluation of five non-rigid image registration algorithms using the NIREP framework", Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76232L (12 March 2010); https://doi.org/10.1117/12.844616
Lens.org Logo
CITATIONS
Cited by 4 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image registration

Image segmentation

Databases

Error analysis

Detection and tracking algorithms

Image analysis

Image processing algorithms and systems

RELATED CONTENT


Back to Top