State estimation with structural priors in fMRI

DOI10.1007/s10851-017-0749-xzbMath1425.94024OpenAlexW2739892463WikidataQ59515187 ScholiaQ59515187MaRDI QIDQ1703167

Ville-Veikko Wettenhovi, Mikko Kettunen, Olli Gröhn, Joanna Huttunen, Ville Kolehmainen, Marko Vauhkonen

Publication date: 1 March 2018

Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10851-017-0749-x

zbMATH Keywords

total variationKalman filterfunctional magnetic resonance imaging (fMRI)GPUradial MRIstructural prior

Mathematics Subject Classification ID

Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (1)

State estimation of time-varying MRI with radial golden angle sampling

Uses Software

• LSQR
• MRI Simulation and Reconstruction
• CRAIG

Cites Work

• Nonlinear total variation based noise removal algorithms
• Incorporating structural prior information and sparsity into EIT using parallel level sets
• Statistical and computational inverse problems.
• Incremental activation detection for real-time fMRI series using robust Kalman filter
• LSQR: An Algorithm for Sparse Linear Equations and Sparse Least Squares
• Electrical impedance tomography with basis constraints
• Block-iterative interior point optimization methods for image reconstruction from limited data
• LS-CS-Residual (LS-CS): Compressive Sensing on Least Squares Residual
• State estimation and inverse problems in electrical impedance tomography: observability, convergence and regularization

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