Abstract
Evaluating registration algorithms is difficult due to the lack of gold standard in most clinical procedures. The bronze standard is a real-data based statistical method providing an alternative registration reference through a computationally intensive image database registration procedure. We propose in this paper an efficient implementation of this method through a grid-interfaced workflow enactor enabling the concurrent processing of hundreds of image registrations in a couple of hours only. The performances of two different grid infrastructures were compared. We computed the accuracy of 4 different rigid registration algorithms on longitudinal MRI images of brain tumors. Results showed an average subvoxel accuracy of 0.4 mm and 0.15 degrees in rotation.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Jannin, P., et al.: Validation of medical image processing in image-guided therapy. IEEE TMI 21(12), 1445–1449 (2002)
Hellier, P., et al.: Retrospective evaluation of intersubject brain registration. IEEE Trans Med Imaging 22(9), 1120–1130 (2003)
Holden, M., et al.: Voxel similarity measures for 3D serial MR brain image registration. IEEE Trans. Med. Imaging 19(2), 94–102 (2000)
Roche, A., et al.: Rigid registration of 3D ultrasound with MR images: a new approach combining intensity and gradient information. IEEE TMI 20(10), 1038–1049 (2001)
Warfield, S.K., et al.: Simultaneous truth and perf. level estimation (staple): an algorithm for the validation of image segmentation. IEEE TMI 23(7), 903–921 (2004)
Pennec, X., et al.: Feature-based Registration of Medical Images: Estimation and Validation of the Pose Accuracy. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 1107–1114. Springer, Heidelberg (1998)
Pennec, X., et al.: Intrinsic Statistics on Riemannian Manifolds: Basic Tools for Geometric Measurements. J. of Math. Imaging and Vision (to appear, 2006)
Oinn, I., et al.: Taverna: a tool for the composition and enactment of bioinformatics workflows. Bioinformatics journal 17(20), 3045–3054 (2004)
Glatard, T., et al.: Efficient services composition for grid-enabled data-intensive applications. In: Proc. of HPDC 2006, pp. 333–334 (2006)
Ourselin, S., et al.: Block matching: A general framework to improve robustness of rigid registration. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 557–566. Springer, Heidelberg (2000)
Pennec, X., et al.: Landmark-based registration using differential geometric features, ch. 31. In: Handbook of Medical Imaging, pp. 499–513. Acad. Press (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Glatard, T., Pennec, X., Montagnat, J. (2006). Performance Evaluation of Grid-Enabled Registration Algorithms Using Bronze-Standards. In: Larsen, R., Nielsen, M., Sporring, J. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006. MICCAI 2006. Lecture Notes in Computer Science, vol 4191. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11866763_19
Download citation
DOI: https://doi.org/10.1007/11866763_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44727-6
Online ISBN: 978-3-540-44728-3
eBook Packages: Computer ScienceComputer Science (R0)