Abstract
This paper describes the functionality and use of the Non-rigid Image Registration Evaluation Program (NIREP) that was developed to make qualitative and quantitative performance comparisons between one or more image registration algorithms. Registration performance is evaluated using common evaluation databases. An evaluation database consists of groups of registered medical images (e.g., one or more MRI modalities, CT, etc.) and annotations (e.g., segmentations, landmarks, contours, etc.) identified by their common image coordinate system. Prior to analysis with NIREP, each algorithm is used to generate pair-wise correspondence maps/transformations between image coordinate systems. NIREP has a highly customizable graphical user interface for displaying images, transformations, segmentations, overlays, differences between images, and differences between transformations. Evaluation statistics built into NIREP are used to compute quantitative algorithm performance reports that include region of interest overlap, intensity variance of images mapped to a reference coordinate system, inverse consistency error and transitivity error.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Christensen, G.E., Johnson, H.J.: Consistent image registration. IEEE Trans. Med. Imaging 20(7), 568–582 (2001)
Christensen, G.E., Johnson, H.J.: Invertibility and transitivity analysis for nonrigid image registration. Journal of Electronic Imaging 12(1), 106–117 (2003)
Johnson, H.J., Christensen, G.E.: Consistent landmark and intensity-based image registration. IEEE Trans. Med. Imaging 21(5), 450–461 (2002)
Christensen, G.E.: Consistent linear-elastic transformations for image matching. In: Kuba, A., Sámal, M. (eds.) IPMI 1999. LNCS, vol. 1613, pp. 224–237. Springer, Heidelberg (1999)
Cao, K.: Local lung tissue expansion analysis based on inverse consistent image registration. Master’s thesis, Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242 (May 2008)
Geng, X., Kumar, D., Christensen, G.E.: Transitive inverse-consistent manifold registration. In: Christensen, G.E., Sonka, M. (eds.) Information Processing in Medical Imaging. LNCS, vol. 3564, pp. 468–479. Springer, Berlin (2005)
Thirion, J.P.: Fast non-rigid matching of 3d medical images. Report 2547, Institut National De Recherche en Informatique Et En Automatique (May 1995)
Thirion, J.: Image matching as a diffusion process: an analogy with maxwell’s demons. Medical Image Analysis 2, 243–260 (1998)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Song, J.H., Christensen, G.E., Hawley, J.A., Wei, Y., Kuhl, J.G. (2010). Evaluating Image Registration Using NIREP. In: Fischer, B., Dawant, B.M., Lorenz, C. (eds) Biomedical Image Registration. WBIR 2010. Lecture Notes in Computer Science, vol 6204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14366-3_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-14366-3_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14365-6
Online ISBN: 978-3-642-14366-3
eBook Packages: Computer ScienceComputer Science (R0)