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TMI
2010
175views more  TMI 2010»
13 years 2 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
TMI
1998
155views more  TMI 1998»
13 years 7 months ago
Spatio-temporal fMRI Analysis using Markov Random Fields
Abstract—Functional magnetic resonance images (fMRI’s) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activa...
Xavier Descombes, Frithjof Kruggel, D. Yves von Cr...
MICCAI
2003
Springer
14 years 8 months ago
Exploratory Identification of Cardiac Noise in fMRI Images
A fast exploratory framework for extracting cardiac noise signals contained in rest-case fMRI images is presented. Highly autocorrelated, independent components of the input time ...
Lilla Zöllei, Lawrence P. Panych, W. Eric L. ...
ICA
2007
Springer
14 years 1 months ago
Subspaces of Spatially Varying Independent Components in fMRI
Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
Jarkko Ylipaavalniemi, Ricardo Vigário
MICCAI
2002
Springer
14 years 8 months ago
Improved Detection Sensitivity in Functional MRI Data Using a Brain Parcelling Technique
We present a comparison between a voxel based approach and a region based technique for detecting brain activation signals in sequences of functional Magnetic Resonance Images (fMR...
Guillaume Flandin, Ferath Kherif, Xavier Pennec, G...