These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

107 related articles for article (PubMed ID: 33018328)

  • 1. A novel spatiotemporal tool for the automatic classification of fMRI noise based on Independent Component Analysis.
    Tassi E; Maggioni E; Cerutti S; Brambilla P; Bianchi AM
    Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():1718-1721. PubMed ID: 33018328
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers.
    Salimi-Khorshidi G; Douaud G; Beckmann CF; Glasser MF; Griffanti L; Smith SM
    Neuroimage; 2014 Apr; 90():449-68. PubMed ID: 24389422
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automatic classification and removal of structured physiological noise for resting state functional connectivity MRI analysis.
    Lee K; Khoo HM; Fourcade C; Gotman J; Grova C
    Magn Reson Imaging; 2019 May; 58():97-107. PubMed ID: 30695721
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Dimensionality of ICA in resting-state fMRI investigated by feature optimized classification of independent components with SVM.
    Wang Y; Li TQ
    Front Hum Neurosci; 2015; 9():259. PubMed ID: 26005413
    [TBL] [Abstract][Full Text] [Related]  

  • 5. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging.
    Griffanti L; Salimi-Khorshidi G; Beckmann CF; Auerbach EJ; Douaud G; Sexton CE; Zsoldos E; Ebmeier KP; Filippini N; Mackay CE; Moeller S; Xu J; Yacoub E; Baselli G; Ugurbil K; Miller KL; Smith SM
    Neuroimage; 2014 Jul; 95():232-47. PubMed ID: 24657355
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Correlating Resting-State Functional Magnetic Resonance Imaging Connectivity by Independent Component Analysis-Based Epileptogenic Zones with Intracranial Electroencephalogram Localized Seizure Onset Zones and Surgical Outcomes in Prospective Pediatric Intractable Epilepsy Study.
    Boerwinkle VL; Mohanty D; Foldes ST; Guffey D; Minard CG; Vedantam A; Raskin JS; Lam S; Bond M; Mirea L; Adelson PD; Wilfong AA; Curry DJ
    Brain Connect; 2017 Sep; 7(7):424-442. PubMed ID: 28782373
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An automated method for identifying artifact in independent component analysis of resting-state FMRI.
    Bhaganagarapu K; Jackson GD; Abbott DF
    Front Hum Neurosci; 2013; 7():343. PubMed ID: 23847511
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Group information guided ICA for fMRI data analysis.
    Du Y; Fan Y
    Neuroimage; 2013 Apr; 69():157-97. PubMed ID: 23194820
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automatic independent component labeling for artifact removal in fMRI.
    Tohka J; Foerde K; Aron AR; Tom SM; Toga AW; Poldrack RA
    Neuroimage; 2008 Feb; 39(3):1227-45. PubMed ID: 18042495
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Objective selection of epilepsy-related independent components from EEG data.
    Abreu R; Leite M; Leal A; Figueiredo P
    J Neurosci Methods; 2016 Jan; 258():67-78. PubMed ID: 26484785
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Analysis of fMRI data by blind separation into independent spatial components.
    McKeown MJ; Makeig S; Brown GG; Jung TP; Kindermann SS; Bell AJ; Sejnowski TJ
    Hum Brain Mapp; 1998; 6(3):160-88. PubMed ID: 9673671
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Partner-matching for the automated identification of reproducible ICA components from fMRI datasets: algorithm and validation.
    Wang Z; Peterson BS
    Hum Brain Mapp; 2008 Aug; 29(8):875-93. PubMed ID: 18058813
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multivariate analysis of neuronal interactions in the generalized partial least squares framework: simulations and empirical studies.
    Lin FH; McIntosh AR; Agnew JA; Eden GF; Zeffiro TA; Belliveau JW
    Neuroimage; 2003 Oct; 20(2):625-42. PubMed ID: 14568440
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Temporally constrained ICA with threshold and its application to fMRI data.
    Long Z; Wang Z; Zhang J; Zhao X; Yao L
    BMC Med Imaging; 2019 Jan; 19(1):6. PubMed ID: 30654748
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Classification of spatially unaligned fMRI scans.
    Anderson A; Dinov ID; Sherin JE; Quintana J; Yuille AL; Cohen MS
    Neuroimage; 2010 Feb; 49(3):2509-19. PubMed ID: 19712744
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A robust classifier to distinguish noise from fMRI independent components.
    Sochat V; Supekar K; Bustillo J; Calhoun V; Turner JA; Rubin DL
    PLoS One; 2014; 9(4):e95493. PubMed ID: 24748378
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A new ICA-based fingerprint method for the automatic removal of physiological artifacts from EEG recordings.
    Tamburro G; Fiedler P; Stone D; Haueisen J; Comani S
    PeerJ; 2018; 6():e4380. PubMed ID: 29492336
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Hand classification of fMRI ICA noise components.
    Griffanti L; Douaud G; Bijsterbosch J; Evangelisti S; Alfaro-Almagro F; Glasser MF; Duff EP; Fitzgibbon S; Westphal R; Carone D; Beckmann CF; Smith SM
    Neuroimage; 2017 Jul; 154():188-205. PubMed ID: 27989777
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Consistency of independent component analysis for FMRI.
    Zhao W; Li H; Hu G; Hao Y; Zhang Q; Wu J; Frederick BB; Cong F
    J Neurosci Methods; 2021 Mar; 351():109013. PubMed ID: 33316320
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Spatiotemporal multiscale ICA could invariantly extract task (motor) modes from wavelet subbands of fMRI data.
    Chen Z; Chen Z
    Comput Methods Programs Biomed; 2021 Sep; 208():106249. PubMed ID: 34218171
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.