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TMI
1998
155views more  TMI 1998»
13 years 5 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...
ISBI
2004
IEEE
14 years 6 months ago
Probabilistic ICA for fMRI
Independent Component Analysis is becoming a popular exploratory method for analysing complex data such as that from FMRI experiments. The application of such `model-free' me...
Christian Beckmann
TMI
2010
175views more  TMI 2010»
13 years 23 hour 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
ICASSP
2007
IEEE
13 years 11 months ago
Spatial Mixture Modelling for the Joint Detection-Estimation of Brain Activity in fMRI
— Within-subject analysis in event-related functional Magnetic Resonance Imaging (fMRI) first relies on (i) a detection step to localize which parts of the brain are activated b...
Thomas Vincent, Philippe Ciuciu, Jérô...
ICML
2006
IEEE
14 years 6 months ago
Hidden process models
We introduce Hidden Process Models (HPMs), a class of probabilistic models for multivariate time series data. The design of HPMs has been motivated by the challenges of modeling h...
Rebecca Hutchinson, Tom M. Mitchell, Indrayana Rus...