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Authors: M. Bartés-Serrallonga 1 ; J. M. Serra-Grabulosa 2 ; A. Adan 3 ; C. Falcón 4 ; N. Bargalló 5 and J. Solé-Casals 1

Affiliations: 1 University of Vic, Spain ; 2 Universitat de Barcelona and Institut d’ Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Spain ; 3 Universitat de Barcelona, Institute for Brain and Cognition and Behaviour (IR3C), Spain ; 4 Institut d’ Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS) and CIBER-BBN, Spain ; 5 Hospital Clínic de Barcelona, Spain

Keyword(s): Adaptive Smoothing, fMRI, Wiener Filter, Smoothing, Gaussian Kernel, Noise.

Abstract: One problem of fMRI images is that they include some noise coming from many other sources like the heart beat, breathing and head motion artifacts. All these sources degrade the data and can cause wrong results in the statistical analysis. In order to reduce as much as possible the amount of noise and to improve signal detection, the fMRI data is spatially smoothed prior to the analysis. The most common and standardized method to do this task is by using a Gaussian filter. The principal problem of this method is that some regions may be under-smoothed, while others may be over-smoothed. This is caused by the fact that the extent of smoothing is chosen independently of the data and is assumed to be equal across the image. To avoid these problems, we suggest in our work to use an adaptive Wiener filter which smooths the images adaptively, performing a little smoothing where variance is large and more smoothing where the variance is small. In general, the results that we obtained with t he adaptive filter are better than those obtained with the Gaussian kernel. In this paper we compare the effects of the smoothing with a Gaussian kernel and with an adaptive Wiener filter, in order to demonstrate the benefits of the proposed approach. (More)


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Paper citation in several formats:
Bartés-Serrallonga, M.; M. Serra-Grabulosa, J.; Adan, A.; Falcón, C.; Bargalló, N. and Solé-Casals, J. (2012). Adaptive Smoothing Applied to fMRI Data. In Proceedings of the 4th International Joint Conference on Computational Intelligence (IJCCI 2012) - SSCN; ISBN 978-989-8565-33-4; ISSN 2184-3236, SciTePress, pages 677-683. DOI: 10.5220/0004182306770683

author={M. Bartés{-}Serrallonga. and J. {M. Serra{-}Grabulosa}. and A. Adan. and C. Falcón. and N. Bargalló. and J. Solé{-}Casals.},
title={Adaptive Smoothing Applied to fMRI Data},
booktitle={Proceedings of the 4th International Joint Conference on Computational Intelligence (IJCCI 2012) - SSCN},


JO - Proceedings of the 4th International Joint Conference on Computational Intelligence (IJCCI 2012) - SSCN
TI - Adaptive Smoothing Applied to fMRI Data
SN - 978-989-8565-33-4
IS - 2184-3236
AU - Bartés-Serrallonga, M.
AU - M. Serra-Grabulosa, J.
AU - Adan, A.
AU - Falcón, C.
AU - Bargalló, N.
AU - Solé-Casals, J.
PY - 2012
SP - 677
EP - 683
DO - 10.5220/0004182306770683
PB - SciTePress