FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1975172680> ?p ?o ?g. }

• W1975172680 endingPage "2884" @default.
• W1975172680 startingPage "2867" @default.
• W1975172680 abstract "We present a novel integrated wavelet-domain based framework (w-ICA) for 3-D denoising functional magnetic resonance imaging (fMRI) data followed by source separation analysis using independent component analysis (ICA) in the wavelet domain. We propose the idea of a 3-D wavelet-based multi-directional denoising scheme where each volume in a 4-D fMRI data set is sub-sampled using the axial, sagittal and coronal geometries to obtain three different slice-by-slice representations of the same data. The filtered intensity value of an arbitrary voxel is computed as an expected value of the denoised wavelet coefficients corresponding to the three viewing geometries for each sub-band. This results in a robust set of denoised wavelet coefficients for each voxel. Given the de-correlated nature of these denoised wavelet coefficients, it is possible to obtain more accurate source estimates using ICA in the wavelet domain. The contributions of this work can be realized as two modules: First, in the analysis module we combine a new 3-D wavelet denoising approach with signal separation properties of ICA in the wavelet domain. This step helps obtain an activation component that corresponds closely to the true underlying signal, which is maximally independent with respect to other components. Second, we propose and describe two novel shape metrics for post-ICA comparisons between activation regions obtained through different frameworks. We verified our method using simulated as well as real fMRI data and compared our results against the conventional scheme (Gaussian smoothing + spatial ICA: s-ICA). The results show significant improvements based on two important features: (1) preservation of shape of the activation region (shape metrics) and (2) receiver operating characteristic curves. It was observed that the proposed framework was able to preserve the actual activation shape in a consistent manner even for very high noise levels in addition to significant reduction in false positive voxels." @default.
• W1975172680 created "2016-06-24" @default.
• W1975172680 creator A5000122265 @default.
• W1975172680 creator A5014222092 @default.
• W1975172680 creator A5023159708 @default.
• W1975172680 creator A5032850756 @default.
• W1975172680 creator A5060798483 @default.
• W1975172680 creator A5075355229 @default.
• W1975172680 date "2011-02-01" @default.
• W1975172680 modified "2023-10-16" @default.
• W1975172680 title "Wavelet-based fMRI analysis: 3-D denoising, signal separation, and validation metrics" @default.
• W1975172680 cites W1812167874 @default.
• W1975172680 cites W1853799209 @default.
• W1975172680 cites W1965551074 @default.
• W1975172680 cites W1974269433 @default.
• W1975172680 cites W1991118037 @default.
• W1975172680 cites W2016444985 @default.
• W1975172680 cites W2018887912 @default.
• W1975172680 cites W2022905067 @default.
• W1975172680 cites W2030521421 @default.
• W1975172680 cites W2034464268 @default.
• W1975172680 cites W2035843433 @default.
• W1975172680 cites W2046457215 @default.
• W1975172680 cites W2050955927 @default.
• W1975172680 cites W2054121225 @default.
• W1975172680 cites W2059784307 @default.
• W1975172680 cites W2070400981 @default.
• W1975172680 cites W2097271689 @default.
• W1975172680 cites W2108207814 @default.
• W1975172680 cites W2113506774 @default.
• W1975172680 cites W2116649573 @default.
• W1975172680 cites W2120364003 @default.
• W1975172680 cites W2132726663 @default.
• W1975172680 cites W2132984323 @default.
• W1975172680 cites W2136017820 @default.
• W1975172680 cites W2138018102 @default.
• W1975172680 cites W2144579212 @default.
• W1975172680 cites W2146842127 @default.
• W1975172680 cites W2148593155 @default.
• W1975172680 cites W2151635492 @default.
• W1975172680 cites W2155708232 @default.
• W1975172680 cites W2158940042 @default.
• W1975172680 cites W2160637922 @default.
• W1975172680 cites W2168015895 @default.
• W1975172680 cites W2169366712 @default.
• W1975172680 doi "https://doi.org/10.1016/j.neuroimage.2010.10.063" @default.
• W1975172680 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3058245" @default.
• W1975172680 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/21034833" @default.
• W1975172680 hasPublicationYear "2011" @default.
• W1975172680 type Work @default.
• W1975172680 sameAs 1975172680 @default.
• W1975172680 citedByCount "34" @default.
• W1975172680 countsByYear W19751726802012 @default.
• W1975172680 countsByYear W19751726802013 @default.
• W1975172680 countsByYear W19751726802014 @default.
• W1975172680 countsByYear W19751726802015 @default.
• W1975172680 countsByYear W19751726802016 @default.
• W1975172680 countsByYear W19751726802017 @default.
• W1975172680 countsByYear W19751726802018 @default.
• W1975172680 countsByYear W19751726802020 @default.
• W1975172680 countsByYear W19751726802021 @default.
• W1975172680 countsByYear W19751726802022 @default.
• W1975172680 countsByYear W19751726802023 @default.
• W1975172680 crossrefType "journal-article" @default.
• W1975172680 hasAuthorship W1975172680A5000122265 @default.
• W1975172680 hasAuthorship W1975172680A5014222092 @default.
• W1975172680 hasAuthorship W1975172680A5023159708 @default.
• W1975172680 hasAuthorship W1975172680A5032850756 @default.
• W1975172680 hasAuthorship W1975172680A5060798483 @default.
• W1975172680 hasAuthorship W1975172680A5075355229 @default.
• W1975172680 hasBestOaLocation W19751726802 @default.
• W1975172680 hasConcept C120317606 @default.
• W1975172680 hasConcept C121927907 @default.
• W1975172680 hasConcept C127162648 @default.
• W1975172680 hasConcept C153180895 @default.
• W1975172680 hasConcept C154945302 @default.
• W1975172680 hasConcept C155777637 @default.
• W1975172680 hasConcept C163294075 @default.
• W1975172680 hasConcept C196216189 @default.
• W1975172680 hasConcept C31258907 @default.
• W1975172680 hasConcept C31972630 @default.
• W1975172680 hasConcept C33923547 @default.
• W1975172680 hasConcept C3770464 @default.
• W1975172680 hasConcept C41008148 @default.
• W1975172680 hasConcept C47432892 @default.
• W1975172680 hasConcept C51432778 @default.
• W1975172680 hasConcept C54170458 @default.
• W1975172680 hasConceptScore W1975172680C120317606 @default.
• W1975172680 hasConceptScore W1975172680C121927907 @default.
• W1975172680 hasConceptScore W1975172680C127162648 @default.
• W1975172680 hasConceptScore W1975172680C153180895 @default.
• W1975172680 hasConceptScore W1975172680C154945302 @default.
• W1975172680 hasConceptScore W1975172680C155777637 @default.
• W1975172680 hasConceptScore W1975172680C163294075 @default.
• W1975172680 hasConceptScore W1975172680C196216189 @default.
• W1975172680 hasConceptScore W1975172680C31258907 @default.
• W1975172680 hasConceptScore W1975172680C31972630 @default.
• W1975172680 hasConceptScore W1975172680C33923547 @default.

• next