In this paper the problem of BOLD detection is addressed. The focus here is on non-negative matrix factorization (NMF), which is a data driven method and ...

Sep 3, 2011 · The simulation results on both synthetic and real fMRI data show that applying the proposed constraint improves the BOLD detection performance.

In this paper the problem of BOLD detection is addressed. The focus here is on non-negative matrix factorization (NMF), which is a data driven method and ...

In this paper the problem of BOLD detection is addressed. The focus here is on non-negative matrix factorization (NMF), which is a data driven method and ...

Feb 17, 2022 · In this study, we proposed a new spatial constrained NMF method ... “A constrained NMF algorithm for bold detection in FMRI,” in ...

DocumentCode : 2491346 · Title : A new spatially constrained NMF with application to fMRI · Author : Ferdowsi, Saideh ; Abolghasemi, Vahid ; Makkiabadi, Bahador ; ...

A new spatially constrained NMF with application to fMRI. S Ferdowsi, V Abolghasemi, B Makkiabadi, S Sanei. 2011 Annual International Conference of the IEEE ...

We compared ICA, K-SVD, NMF, and L1-Regularized Learning for encoding brain components within an fMRI scan.

Oct 22, 2024 · In this paper, we introduce a Spatially Correlated Nonnegative Matrix Factorization algorithm, which explicitly models the spatial correlation ...

Inspired by this method, we presented a new spatial constrained non-negative matrix decomposition (SCNMF) approach to obtain <italic>a priori</italic> ...