Paper Info
Title
Extracting the haemodynamic response function from fMRI time series using Fourier-wavelet regularised deconvolution with orthogonal spline wavelets
Abstract
We describe a method to extract the haemodynamic response func- tion (HRF) from functional magnetic resonance imaging (fMRI) time series based on Fourier-wavelet regularised deconvolution (ForWaRD), and introduce a simple model for the HRF. The HRF extraction algorithm extends the ForWaRD algorithm by introduc- ing a more efficient computation in the case of very long wavelet filters. We compute shift-invariant discrete wavelet transforms (SI- DWT) in the frequency domain, and apply ForWaRD using orthog- onal spline wavelets. Extraction and modelling of subject-specific HRFs is demonstrated, as well as the use of these HRFs in a sub- sequent brain activation analysis. Temporal responses are predicted by using the extracted HRF coefficients. The resulting activation maps show the effectiveness of the proposed method.
Year
Venue
Keywords
2006
EUSIPCO
fourier transforms,biomedical mri,brain,deconvolution,discrete wavelet transforms,feature extraction,haemodynamics,medical image processing,time series,fourier-wavelet regularised deconvolution,brain activation analysis,fmri time series,frequency domain,functional magnetic resonance imaging,haemodynamic response function coefficients,orthogonal spline wavelets,shift-invariant discrete wavelet transforms,subject-specific hrf extraction
Field
DocType
ISSN
Spline (mathematics),Frequency domain,Pattern recognition,Forward algorithm,Deconvolution,Speech recognition,Fourier transform,Discrete wavelet transform,Artificial intelligence,Mathematics,Wavelet,Wavelet transform
Conference
2219-5491
Citations 
PageRank 
References 
1
0.63
11
Authors
2
Name
Order
Citations
PageRank
Alle-Meije Wink1938.15
Roerdink, J.B.T.M.21558.00