Abstract
The presence of cerebral activation may bias motion correction estimates when registering FMRI time series. This problem may be solved through the use of specific registration methods, which incorporate or down-weight cerebral activation confounding signals during registration. In this paper, we evaluate the performance of different registration methods specifically designed to deal with the problem of activation presence. The methods studied here yielded better results than the traditional approaches based on least square metrics, almost totally eliminating the activation-related confounds.
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
Freire, L., Mangin, J.-F.: Motion correction algorithms may create spurious brain activations in the absence of subject motion. NeuroImage 14, 709–722 (2001)
Black, M., Rangarajan, A.: On the unification of line processes, outlier rejection, and robust statistics with applications in early vision. International Journal of Computer Vision 19, 57–91 (1996)
Nikou, C., Heitz, F., Armspach, J.-P., Namer, I.-J., Grucker, D.: Registration of MR/MR and MR/SPECT brain images by fast stochastic optimization of robust voxel similarity measures. NeuroImage 8(1), 30–43 (1998)
Freire, L., Roche, A., Mangin, J.-F.: What is the best similarity measure for motion correction of fmri time series? IEEE Trans. on Medical Imaging 21(5), 470–484 (2002)
Freire, L., Mangin, J.-F.: Two stage alignment of fmri time series using the experiment profile to discard activation related bias. Medical Image Computing and Computer-Assisted Intervention, 663–670 (2002)
Orchard, J., Greif, C., Golub, G., Bjornson, B., Atkins, M.: Simultaneous registration and activation detection for fMRI. IEEE Trans. on Medical Imaging 22(11), 1427–1435 (2003)
Unser, M., Aldroubi, A., Eden, M.: B-spline signal processing: Part I-theory. IEEE Trans Signal Process 41, 821–833 (1993)
Press, W., Teukolsky, S., Vetterling, W., Flannery, B.: Numerical Recipies in C, 2nd edn. Cambridge University Press, Cambridge (1995)
Studholme, C., Constable, R., Duncan, J.: Accurate alignment of functional EPI data to anatomical MRI using a physics-based distortion model. IEEE Trans. on Medical Imaging 19(11), 1115–1127 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Freire, L., Orchard, J., Jenkinson, M., Mangin, JF. (2004). Reducing Activation-Related Bias in FMRI Registration. In: Yang, GZ., Jiang, TZ. (eds) Medical Imaging and Augmented Reality. MIAR 2004. Lecture Notes in Computer Science, vol 3150. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28626-4_34
Download citation
DOI: https://doi.org/10.1007/978-3-540-28626-4_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22877-6
Online ISBN: 978-3-540-28626-4
eBook Packages: Springer Book Archive