Application of the Kalman Filter in Functional Magnetic Resonance Image Data

Valcir Farias; Marcus Rocha; Heliton Tavares

doi:10.31686/ijier.vol8.iss9.2657

Authors

Valcir J. da C. Farias Federal University of Pará – Brazil
Marcus P. C. Rocha Federal University of Pará – Brazil
Heliton Tavares Federal University of Pará

DOI:

https://doi.org/10.31686/ijier.vol8.iss9.2657

Keywords:

Kalman Filter, Temporal Filtering, fMRI, Self-organizing maps

Abstract

The Kalman-Bucy filter was applied on the preprocessing of the functional magnetic resonance image-fMRI. Numerical simulations of hemodynamic response added Gaussian noise were performed to evaluate the performance of the filter. After the proceeding was applied in auditory real data. The Kohonen’s self-organized map was employed as tools to compare the performance of the Kalman’s filter with another type of pre-processing. The results of the application of Kalman-Bucy filter for simulated data and real auditory data showed that it can be used as a tool in the temporal filtering step in fMRI data.

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Author Biographies

Valcir J. da C. Farias, Federal University of Pará – Brazil

Faculty of Statistics- Institute of Exact and Natural Sciences
Marcus P. C. Rocha, Federal University of Pará – Brazil

Faculty of Mathematics- Institute of Exact and Natural Sciences
Heliton Tavares, Federal University of Pará

Faculty of Statistics- Institute of Exact and Natural Sciences

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