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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
TMI
2010
182views more  TMI 2010»
13 years 3 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
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
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
MICCAI
2009
Springer
14 years 5 months ago
Nonparametric Mean Shift Functional Detection in the Functional Space for Task and Resting-state fMRI
In functional Magnetic Resonance Imaging (fMRI) data analysis, normalization of time series is an important and sometimes necessary preprocessing step in many widely used methods. ...
Jian Cheng, Feng Shi, Kun Wang, Ming Song, Jiefeng...