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A spatially constrained low-rank matrix factorization for the ...
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We propose a new matrix recovery framework to partition brain activity using time series of resting-state functional Magnetic Resonance Imaging (fMRI).
a spatially constrained low-rank matrix factorization
European Association For Signal Processing
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European Association For Signal Processing
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由 A Benichoux 著作被引用 1 次 — A spatial brain parcellation is a partition of the human cere- bral cortex into distinct cortical regions. Different approaches to brain parcellation shed light ...
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Alexis Benichoux
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A spatially constrained low-rank matrix factorization for the functional parcellation of the brain. A Benichoux, T Blumensath. 2014 22nd European Signal ...
Spatially constrained hierarchical parcellation of the brain ...
National Institutes of Health (NIH) (.gov)
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National Institutes of Health (NIH) (.gov)
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由 T Blumensath 著作2013被引用 280 次 — We propose a novel computational strategy to partition the cerebral cortex into disjoint, spatially contiguous and functionally homogeneous parcels.
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Blumensath (first grant)-Constrained low rank matrix ...
University of Southampton
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University of Southampton
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A spatially constrained low-rank matrix factorization for the functional parcellation of the brain. A. Benichoux & T. Blumensath, 2014, Proc. 22nd European ...
Estimating Functional Brain Network with Low-Rank ...
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由 Y Du 著作2021被引用 2 次 — In this paper, we propose a novel method for improving the estimated FBNs utilizing matrix factorization (MF).
Low rank and sparsity constrained method for identifying ...
PLOS
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由 P Aggarwal 著作2018被引用 11 次 — In this paper, large-scale overlapping fBNs are identified on resting state fMRI data by employing non-negative matrix factorization. Our ...
(PDF) A whole brain fMRI atlas generated via spatially ...
ResearchGate
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2024年10月22日 — This article introduces a data-driven method for generating an ROI atlas by parcellating whole brain resting-state fMRI data into spatially coherent regions of ...
Deconvolving Complex Neuronal Networks into ...
arXiv
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arXiv
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2024年7月3日 — We use fMRI data to formulate and solve the problem of deconvolving task-specific aggregate neuronal networks into a set of basic building ...
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