SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA

Authors

  • Karsten Rodenacker
  • Klaus Hahn
  • Gerhard Winkler
  • Dorothea P Auer

DOI:

https://doi.org/10.5566/ias.v19.p189-194

Keywords:

brain mapping, functional magnetic resonance imaging, non-linear filtering, mathematical morphology, spatio-temporal image analysis

Abstract

Spatio-temporal digital data from fMRI (functional Magnetic Resonance Imaging) are used to analyse and to model brain activation. To map brain functions, a well-defined sensory activation is offered to a test person and the hemodynamic response to neuronal activity is studied. This so-called BOLD effect in fMRI is typically small and characterised by a very low signal to noise ratio. Hence the activation is repeated and the three dimensional signal (multi-slice 2D) is gathered during relatively long time ranges (3-5 min). From the noisy and distorted spatio-temporal signal the expected response has to be filtered out. Presented methods of spatio-temporal signal processing base on non-linear concepts of data reconstruction and filters of mathematical morphology (e.g. alternating sequential morphological filters). Filters applied are compared by classifications of activations.

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Published

2011-05-03

How to Cite

Rodenacker, K., Hahn, K., Winkler, G., & Auer, D. P. (2011). SPATIO-TEMPORAL DATA ANALYSIS WITH NON-LINEAR FILTERS: BRAIN MAPPING WITH fMRI DATA. Image Analysis and Stereology, 19(3), 189–194. https://doi.org/10.5566/ias.v19.p189-194

Issue

Section

Original Research Paper

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