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Fast robust automated brain extraction
TLDR
An automated method for segmenting magnetic resonance head images into brain and non‐brain has been developed and described and examples of results and the results of extensive quantitative testing against “gold‐standard” hand segmentations, and two other popular automated methods.
Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images
TLDR
This paper examines the optimization process in detail and demonstrates that the commonly used multiresolution local optimization methods can, and do, get trapped in local minima.
Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm
TLDR
The authors propose a novel hidden Markov random field (HMRF) model, which is a stochastic process generated by a MRF whose state sequence cannot be observed directly but which can be indirectly estimated through observations.
Correspondence of the brain's functional architecture during activation and rest
Neural connections, providing the substrate for functional networks, exist whether or not they are functionally active at any given moment. However, it is not known to what extent brain regions are
Probabilistic independent component analysis for functional magnetic resonance imaging
TLDR
An integrated approach to probabilistic independent component analysis for functional MRI (FMRI) data that allows for nonsquare mixing in the presence of Gaussian noise is presented and compared to the spatio-temporal accuracy of results obtained from classical ICA and GLM analyses.
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