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Motion Correction Algorithms of the Brain Mapping Community Create Spurious Functional Activations

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Information Processing in Medical Imaging (IPMI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2082))

Abstract

This paper describes several experiments that prove that standard motion correction methods may induce spurious activations in some motion-free fMRI studies. This artefact stems from the fact that activated areas behave like biasing outliers for the least square based measure usually driving such registration methods. This effect is demonstrated first using a motion-free simulated time series including artificial activation-like signal changes. Several additional simulations explore the influence of activation on registration accuracy for a wide-range of simulated misregistrations. The effect is finally highlighted on an actual time series obtained from a 3T magnet. All the experiments are performed using four different realignment methods, which allows us to show that the problem is overcome by methods based on robust similarity measures like mutual information.

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References

  1. Hajnal, J. V., Mayers, R., Oatridge, A., Schwieso, J. E., Young, I. R., and Bydder, G. M.: Artefacts due to stimulus correlated motion in functional imaging of the brain. Magn. Reson. Med. 31 (1994) 289–291

    Article  Google Scholar 

  2. Grootoonk, S., Hutton, C., Ashburner, J., Howseman, A. M., Josephs, O., Rees, G., Friston, K. J., and Turner, R.: Characterization and correction of interpolation effects in the realignment of fMRI time series. NeuroImage, 11 (2000) 49–57

    Article  Google Scholar 

  3. Friston, K. J., Williams, S., Howard, R., Frackowiak, R. S. J., and Turner, R.: Movement-related effects in fMRI time-series. Magn. Reson. Med. 35 (1996) 346–355

    Google Scholar 

  4. Robson, M. D., Gatenby, J. C., Anderson, A.W., and Gore, J. C.: Practical considerations when correcting for movement-related effects present in fMRI time-series. In Proc. ISMRM 5th. Annual Meeting, Vancouver, (1997) 1681

    Google Scholar 

  5. Birn, R. M., Jesmanowicz, A., Cor, R., and Shaker, R.: Correction of dynamic Bz-field artifacts in EPI, in Proc. ISMRM 5th Annual Meeting, Vancouver, (1997) 1913

    Google Scholar 

  6. Wu, D. H., Lewin, J. S., and Duerl, J. L.: Inadequacy of motion correction algorithms in functional MRI: role of susceptibility-induced artefacts. J. Mag. Res. Image. 7 (1997) 365–370

    Article  Google Scholar 

  7. 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

    Article  Google Scholar 

  8. Woods, R. P., Grafton S. T., Holmes C. J., Cherry, S. R., and Mazziotta, J. C.: Automated image registration: I. General methods and intrasubject, intramodality validation. JCAT, 22(1) (1998) 139–152

    Google Scholar 

  9. Wells W. M., Viola P., Atsumi H., and Nakajima S.: Multi-modal volume registration by maximization of mutual information. Medical Image Analysis, 1(1) (1996) 35–51

    Article  Google Scholar 

  10. Maes F., Collignon A. Vanderneulen D., Marchal G., and Suetens P.: Multimodality image registration by maximization of mutual information. IEEE Trans. Med. Imag., 16(2) (1997) 187–198

    Article  Google Scholar 

  11. Viola P. and Wells W. M.: Alignment by maximization of mutual information. International Journal of Computer Vision, 24(2) (1997) 137–154

    Article  Google Scholar 

  12. Studholme C., Hill D. L. G., and Hawkes D. J.: Automated three-dimensional registration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. Medical Physics, 24(1) (1997) 25–35

    Article  Google Scholar 

  13. Meyer C. R., Boes J. L., Kim B., Bland P. H., Zasadny K. R., Kison P. V., Koral K., Frey K. A., and Wahl R. L.: Demonstration of accuracy and clinical versatility of mutual information for automatic multimodality image fusion using affine and thin-plate spline warped geometric deformations. Medical Image Analysis, 1(3) (1997) 195–206

    Article  Google Scholar 

  14. Jezzard P. and Clare S.: Sources of distortions in functional MRI data. Hum. Brain Mapp. 8 (1999) 80–85

    Article  Google Scholar 

  15. Jiang A. P., Kennedy D. N., Baker J. R., Weiskoff R. M., Tootell R. B. H., Woods R. P., Benson R. R., Kwong K. K., Brady T. J., Rosen B. R., and Belliveau J. W.: Motion detection and correction in functional MR imaging. Hum. Brain Mapp. 3 (1995) 224–235

    Article  Google Scholar 

  16. Frouin V., Messegue E., and Mangin J.-F.: Assessment of two fMRI motion correction algorithms. Hum. Brain Mapp. 5 (1997) S458

    Google Scholar 

  17. West J. et al.: Comparison and evaluation of retrospective intermodality brain image registration techniques. J. Comput. Assist. Tomogr. 21(4) (1997) 554–566

    Article  Google Scholar 

  18. Holden M., Hill D. L. G., Denton E. R. E., Jarosz J. M., Cox T. C. S., Rohlfing T., Goodey J., and Hawkes D. J.: Voxel similarity measures for 3D serial MR brain image registration, IEEE Trans. Med. Imag. 19(2) (2000) 94–102.

    Article  Google Scholar 

  19. Friston K. J., Ahsburner 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

    Article  Google Scholar 

  20. Unser M., Aldroubi A., and Eden M.: B-Spline Signal Processing: Part I-Theory, IEEE Transactions on Signal Processing, 41(2) (1993) 821–832

    Article  MATH  Google Scholar 

  21. Unser M., Aldroubi A., and Eden M.: B-Spline Signal Processing: Part II-Efficient Design and Applications, IEEE Transactions on Signal Processing, (2) (1993) 834–848

    Article  Google Scholar 

  22. Andersson J. L. R.: How to estimate global activity independent of changes in local activity, NeuroImage, 6 (1997) 237–244

    Article  Google Scholar 

  23. Maintz J. B. A. and Viergever M. A.: A survey of medical image registration. Medical Image Analysis, 2(1) (1998) 1–36

    Article  Google Scholar 

  24. Roche A., Malandain G., Pennec X., and Ayache N.: The correlation ratio as a new similarity measure for multimodal image registration. In Proc. MICCAI98, LNCS-1496, Springer Verlag, (1998) 1115–1124

    Google Scholar 

  25. Studholme C., Hill D. L. G., and Hawkes D. J.: An overlap invariant entropy measure of 3D medical image alignment. Pattern Recognition, 32(1) (1999) 71–86

    Article  Google Scholar 

  26. Pluim J. P. W., Maintz J. B., and Viergever M.: Image registration by maximization of combined mutual information and gradient information, In Proc. MICCAI00, LNCS-1935, Springer Verlag, (2000) 452–461

    Google Scholar 

  27. Nicou 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(1) (1998) 30–43

    Article  Google Scholar 

  28. Roche A., Pennec X., Rudolph M., Auer D. P., Malandain G., Ourselin S., Auer L. M., and Ayache N.: Generalized Correlation Ratio for Rigid Registration of 3D Ultrasound with MR images. In Proc. MICCAI00, Pittsburgh, USA, LNCS-1935, Springer Verlag (2000) 567–577

    Google Scholar 

  29. Pluim J. P. W., Maintz J. B., and Viergever M.: Interpolation artefacts in mutual information-based image registration, Computer Vision and Image Understanding 77 (2000) 211–232

    Article  Google Scholar 

  30. Jenkinson M., and Smith S. M.: A global method for robust affine registration of brain images, Medical Image Analysis (2001, in press).

    Google Scholar 

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Author information

Authors and Affiliations

  1. Service Hospitalier Frédéric Joliot, CEA, 91401, Orsay, France

    Luis Freire & Jean-François Mangin

  2. Instituto de Medicina Nuclear, FML, 1600, Lisboa, Portugal

    Luis Freire

Authors
  1. Luis Freire
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  2. Jean-François Mangin
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Editor information

Editors and Affiliations

  1. Biomedical Engineering, University of California, One Shields Avenue, Davis, CA, 95616, USA

    Michael F. Insana

  2. Signal and Image Processing Institute, University of Southern California, 3740 McClintock Avenue, Los Angeles, CA, 90089-2564, USA

    Richard M. Leahy

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© 2001 Springer-Verlag Berlin Heidelberg

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Freire, L., Mangin, JF. (2001). Motion Correction Algorithms of the Brain Mapping Community Create Spurious Functional Activations. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_27

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  • DOI: https://doi.org/10.1007/3-540-45729-1_27

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42245-7

  • Online ISBN: 978-3-540-45729-9

  • eBook Packages: Springer Book Archive

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