Variational solution to the joint detection estimation of brain activity in fMRI.
Med Image Comput Comput Assist Interv
; 14(Pt 2): 260-8, 2011.
Article
em En
| MEDLINE
| ID: mdl-21995037
ABSTRACT
We address the issue of jointly detecting brain activity and estimating underlying brain hemodynamics from functional MRI data. We adopt the so-called Joint Detection Estimation (JDE) framework that takes spatial dependencies between voxels into account. We recast the JDE into a missing data framework and derive a Variational Expectation-Maximization (VEM) algorithm for its inference. It follows a new algorithm that has interesting advantages over the previously used intensive simulation methods (Markov Chain Monte Carlo, MCMC) tests on artificial data show that the VEM-JDE is more robust to model mis-specification while additional tests on real data confirm that it achieves similar performance in much less computation time.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Processamento de Imagem Assistida por Computador
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Encéfalo
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Mapeamento Encefálico
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Imageamento por Ressonância Magnética
Tipo de estudo:
Diagnostic_studies
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Health_economic_evaluation
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Prognostic_studies
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Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2011
Tipo de documento:
Article