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MICCAI
2007
Springer
14 years 5 months ago
Detection of Spatial Activation Patterns as Unsupervised Segmentation of fMRI Data
In functional connectivity analysis, networks of interest are defined based on correlation with the mean time course of a user-selected `seed' region. In this work we propose ...
Polina Golland, Yulia Golland, Rafael Malach
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
MICCAI
2009
Springer
14 years 5 months ago
Functional Segmentation of fMRI Data Using Adaptive Non-negative Sparse PCA (ANSPCA)
We propose a novel method for functional segmentation of fMRI data that incorporates multiple functional attributes such as activation effects and functional connectivity, under a ...
Bernard Ng, Rafeef Abugharbieh, Martin J. McKeow...
MICCAI
2006
Springer
14 years 5 months ago
A Nonparametric Bayesian Approach to Detecting Spatial Activation Patterns in fMRI Data
Traditional techniques for statistical fMRI analysis are often based on thresholding of individual voxel values or averaging voxel values over a region of interest. In this paper w...
Hal S. Stern, Padhraic Smyth, Seyoung Kim
MICCAI
1999
Springer
13 years 8 months ago
Statistical Segmentation of fMRI Activations Using Contextual Clustering
Abstract. A central problem in the analysis of functional magnetic resonance imaging (fMRI) data is the reliable detection and segmentation of activated areas. Often this goal is a...
Eero Salli, Ari Visa, Hannu J. Aronen, Antti Korve...