publication . Article . 2018

Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion

Basile Pinsard; Basile Pinsard; Basile Pinsard; Arnaud Boutin; Arnaud Boutin; Julien Doyon; Julien Doyon; Habib Benali; Habib Benali; Habib Benali;
  • Published: 01 Apr 2018
Abstract
Functional MRI acquisition is sensitive to subjects' motion that cannot be fully constrained. Therefore, signal corrections have to be applied a posteriori in order to mitigate the complex interactions between changing tissue localization and magnetic fields, gradients and readouts. To circumvent current preprocessing strategies limitations, we developed an integrated method that correct motion and spatial low-frequency intensity fluctuations at the level of each slice in order to better fit the acquisition processes. The registration of single or multiple simultaneously acquired slices is achieved online by an Iterated Extended Kalman Filter, favoring the robus...
Subjects
ACM Computing Classification System: ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
free text keywords: fMRI, motion correction, distortion correction, denoising, BOLD, visualization, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Methods, Psychology, Information representation, Neuroscience, A priori and a posteriori, Signal variability, Explained variation, Extended Kalman filter, Noise reduction, Preprocessor, Artificial intelligence, business.industry, business, Pattern recognition
Funded by
CIHR
Project
  • Funder: Canadian Institutes of Health Research (CIHR)
Communities
Neuroinformatics
50 references, page 1 of 4

Andersson J. L. R.Graham M. S.Drobnjak I.Zhang H.Filippini N.Bastiani M. (2017). Towards a comprehensive framework for movement and distortion correction of diffusion MR images: within volume movement. Neuroimage 152, 450–466. 10.1016/j.neuroimage.2017.02.085 28284799 [OpenAIRE] [PubMed] [DOI]

Andersson J. L. R.Skare S.Ashburner J. (2003). How to correct susceptibility distortions in spin-echo echo-planar images: application to diffusion tensor imaging. Neuroimage 20, 870–888. 10.1016/S1053-8119(03)00336-7 14568458 [OpenAIRE] [PubMed] [DOI]

Avants B. B.Epstein C. L.Grossman M.Gee J. C. (2008). Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12, 26–41. 10.1016/j.media.2007.06.004 17659998 [OpenAIRE] [PubMed] [DOI]

Bierens H. J. (1996). Topics in Advanced Econometrics: Estimation, Testing, and Specification of Cross-Section and Time Series Models. Cambridge: Cambridge University Press.

Bollmann S.Kasper L.Vannesjo S. J.Diaconescu A. O.Dietrich B. E.Gross S.. (2017). Analysis and correction of field fluctuations in fMRI data using field monitoring. Neuroimage 154, 92–105. 10.1016/j.neuroimage.2017.01.014 28077303 [OpenAIRE] [PubMed] [DOI]

Dale A. M.Fischl B.Sereno M. I. (1999). Cortical surface-based analysis: I. segmentation and surface reconstruction. Neuroimage 9, 179–194. 9931268 [PubMed]

El-Sharkawy A. M.Schär M.Bottomley P. A.Atalar E. (2006). Monitoring and correcting spatio-temporal variations of the MR scanner's static magnetic field. MAGMA 19, 223–236. 10.1007/s10334-006-0050-2 17043837 [OpenAIRE] [PubMed] [DOI]

Feinberg D. A.Setsompop K. (2013). Ultra-fast MRI of the human brain with simultaneous multi-slice imaging. J. Magn. Reson. 229, 90–100. 10.1016/j.jmr.2013.02.002 23473893 [OpenAIRE] [PubMed] [DOI]

Ferrante E.Paragios N. (2017). Slice-to-volume medical image registration: a survey. Med. Image Anal. 39(Suppl. C), 101–123. 10.1016/j.media.2017.04.010 28482198 [OpenAIRE] [PubMed] [DOI]

Ferrazzi G.Kuklisova Murgasova M.Arichi T.Malamateniou C.Fox M. J.Makropoulos A.. (2014). Resting State fMRI in the moving fetus: a robust framework for motion, bias field and spin history correction. Neuroimage 101, 555–568. 10.1016/j.neuroimage.2014.06.074 25008959 [OpenAIRE] [PubMed] [DOI]

Fischl B.Sereno M. I.Dale A. M. (1999a). Cortical surface-based analysis: II: inflation, flattening, and a surface-based coordinate system. Neuroimage 9, 195–207. 9931269 [OpenAIRE] [PubMed]

Fischl B.Sereno M. I.Tootell R. B.Dale A. M. (1999b). High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum. Brain Mapp. 8, 272–284. 10619420 [OpenAIRE] [PubMed]

Foerster B. U.Tomasi D.Caparelli E. C. (2005). Magnetic field shift due to mechanical vibration in functional magnetic resonance imaging. Magn. Reson. Med. 54, 1261–1267. 10.1002/mrm.20695 16215962 [OpenAIRE] [PubMed] [DOI]

Gholipour A.Estroff J. A.Warfield S. K. (2010). Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. Med. Imaging 29, 1739–1758. 10.1109/TMI.2010.2051680 20529730 [OpenAIRE] [PubMed] [DOI]

Glasser M. F.Sotiropoulos S. N.Wilson J. A.Coalson T. S.Fischl B.Andersson J. L.. (2013). The minimal preprocessing pipelines for the Human Connectome Project. Neuroimage 80, 105–124. 10.1016/j.neuroimage.2013.04.127 23668970 [OpenAIRE] [PubMed] [DOI]

50 references, page 1 of 4
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue
publication . Article . 2018

Integrated fMRI Preprocessing Framework Using Extended Kalman Filter for Estimation of Slice-Wise Motion

Basile Pinsard; Basile Pinsard; Basile Pinsard; Arnaud Boutin; Arnaud Boutin; Julien Doyon; Julien Doyon; Habib Benali; Habib Benali; Habib Benali;