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TMI
2010
175views more  TMI 2010»
14 years 4 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»
14 years 9 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
15 years 10 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
15 years 3 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
15 years 10 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...