Abstract
In this paper, we show that the standard point of view of the neuroimaging community about fMRI time series alignment should be revisited to overcome the bias induced by activations. We propose to perform a two-stage alignment. The first motion estimation is used to infer a mask of activated areas. The second motion estimation discards these areas during the similarity measure estimations. Simulated and actual time series are used to show that this dedicated approach is more efficient than standard robust similarity measures.
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
Freire, L., and Mangin, J.-F.: Motion correction algorithms may create spurious brain activations in the absence of subject motion. NeuroImage 14, (2001) 709–722
Freire, L., Roche, A. and Mangin, J.-F.: What is the best similarity measure for motion correction of fMRI time series?. IEEE Trans. Med. Imag. 21 (2002) 470–484
Roche, A.: Recalage d’images médicales par inférence statistique. PhD Thesis, Université de Nice-Sophia Antipolis, Projet Epidaure, INRIA, (2001)
Friston, K. J., Ashburner, J., Frith, C. D., Poline, J.-B., Heather, J. D., and Frackowiak, R. S. J.: Spatial registration and normalization of images. Hum. Brain Mapp. 2 (1995) 165–189
Nikou, C., Heitz, F., Armspach, J.-P., Namer, I.-J., and Grucker, D.: Registration of MR/MR and MR/SPECT brain images by fast stochastic optimization of robust voxel similarity measures. NeuroImage 8 (1998) 30–43
Woods, R. P., Cherry, S. R., and Mazziotta, J. C.: Rapid automated algorithm for aligning and reslicing PET images. J. Comput. Assist. Tomogr. 16 (1992) 620–633
Roche, A., Malandain, G., Pennec, X., and Ayache, N.: The correlation ratio as a new similarity measure for multimodal image registration. in Proc. MICCAI’98, 1998, Cambridge, USA, LNCS-1496, Springer Verlag, 1115–1124.
Wells, W. M., Viola, P., Atsumi, H., Nakajima, S., and Kikinis, R.: Multi-modal volume registration by maximization of mutual information. Med. Image Anal. 1 (1996) 35–51
Maes, F., Collignon, A., Vandermeulen, D., Marchal, G., and Suetens, P.: Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imag. 16 (1997) 187–198
Unser, M., Aldroubi, A., and Eden, M.: B-Spline Signal Processing: Part I-Theory. IEEE Trans. Signal Process. 41 (1993) 821–833
Unser, M., Aldroubi, A., and Eden, M.: B-Spline Signal Processing: Part II-Efficient Design and Applications. IEEE Trans. Signal Process. 41 (1993) 834–848
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Freire, L., Mangin, JF. (2002). Two-Stage Alignment of fMRI Time Series Using the Experiment Profile to Discard Activation-Related Bias. In: Dohi, T., Kikinis, R. (eds) Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002. MICCAI 2002. Lecture Notes in Computer Science, vol 2489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45787-9_83
Download citation
DOI: https://doi.org/10.1007/3-540-45787-9_83
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44225-7
Online ISBN: 978-3-540-45787-9
eBook Packages: Springer Book Archive