Self-organizing maps
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
fMRI Study of Cognitive Interference Processing in Females with Fragile X Syndrome
Journal of Cognitive Neuroscience
Extraction of fuzzy features for detecting brain activation from functional MR time-series
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
IEEE Transactions on Information Technology in Biomedicine
Approach and applications of constrained ICA
IEEE Transactions on Neural Networks
Knowledge and intelligent computing system in medicine
Computers in Biology and Medicine
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We propose to use fuzzy c-means clustering with contextual modeling on features extracted from fMRI data for detection of brain activation. Five discriminating features are extracted from fMRI data by using a sequence of temporal-sliding-windows. Fuzzy membership maps of individual subjects obtained through clustering with spatial regularization is capable of taking into account both hemodynamic variability and contextual information of brain activation. The present method outperforms statistical parametric mapping (SPM) approach on experiments with synthetic fMRI data contaminated by both independent and correlated noise. Performance on real fMRI data are comparable to those obtained with SPM.