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ISBI
2006
IEEE
14 years 5 months ago
Joint detection-estimation of brain activity in fMRI using an autoregressive noise model
Different approaches have been considered so far to cope with the temporal correlation of fMRI data for brain activity detection. However, it has been reported that modeling this ...
Jérôme Idier, Jean-Baptiste Poline, P...
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...
MICCAI
2010
Springer
13 years 3 months ago
Detecting Brain Activation in fMRI Using Group Random Walker
Due to the complex noise structure of functional magnetic resonance imaging (fMRI) data, methods that rely on information within a single subject often results in unsatisfactory fu...
Bernard Ng, Ghassan Hamarneh, Rafeef Abugharbieh
ISBI
2004
IEEE
14 years 5 months ago
Incremental Activation Detection in fMRI Series Using Kalman Filtering
We propose a new detection algorithm for functional magnetic resonance imaging (fMRI) data. Our basic idea is to use an extended Kalman filter (EKF) to fit a general linear model ...
Alexis Roche, Jean-Baptiste Poline, Pierre-Jean La...
TMI
2010
175views more  TMI 2010»
12 years 11 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