BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

156 related articles for article (PubMed ID: 21761690)

  • 1. Generalized sparse regularization with application to fMRI brain decoding.
    Ng B; Abugharbieh R
    Inf Process Med Imaging; 2011; 22():612-23. PubMed ID: 21761690
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm.
    Belilovsky E; Gkirtzou K; Misyrlis M; Konova AB; Honorio J; Alia-Klein N; Goldstein RZ; Samaras D; Blaschko MB
    Comput Med Imaging Graph; 2015 Dec; 46 Pt 1():40-46. PubMed ID: 25861834
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Sparse regularization techniques provide novel insights into outcome integration processes.
    Mohr H; Wolfensteller U; Frimmel S; Ruge H
    Neuroimage; 2015 Jan; 104():163-76. PubMed ID: 25467302
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Sparse models for visual image reconstruction from fMRI activity.
    Wang L; Tong L; Yan B; Lei Y; Wang L; Zeng Y; Hu G
    Biomed Mater Eng; 2014; 24(6):2963-9. PubMed ID: 25227003
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sparse representation of group-wise FMRI signals.
    Lv J; Li X; Zhu D; Jiang X; Zhang X; Hu X; Zhang T; Guo L; Liu T
    Med Image Comput Comput Assist Interv; 2013; 16(Pt 3):608-16. PubMed ID: 24505812
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Sparse linear regression for reconstructing muscle activity from human cortical fMRI.
    Ganesh G; Burdet E; Haruno M; Kawato M
    Neuroimage; 2008 Oct; 42(4):1463-72. PubMed ID: 18634889
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Functional segmentation of fMRI data using adaptive non-negative sparse PCA (ANSPCA).
    Ng B; Abugharbieh R; McKeown MJ
    Med Image Comput Comput Assist Interv; 2009; 12(Pt 2):490-7. PubMed ID: 20426148
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A nonparametric bayesian approach to detecting spatial activation patterns in fMRI data.
    Kim S; Smyth P; Stern H
    Med Image Comput Comput Assist Interv; 2006; 9(Pt 2):217-24. PubMed ID: 17354775
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Bayesian analysis of fMRI data with ICA based spatial prior.
    Bathula DR; Tagare HD; Staib LH; Papademetris X; Schultz RT; Duncan JS
    Med Image Comput Comput Assist Interv; 2008; 11(Pt 2):246-54. PubMed ID: 18982612
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Fast bootstrapping and permutation testing for assessing reproducibility and interpretability of multivariate fMRI decoding models.
    Conroy BR; Walz JM; Sajda P
    PLoS One; 2013; 8(11):e79271. PubMed ID: 24244465
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.
    Yourganov G; Schmah T; Churchill NW; Berman MG; Grady CL; Strother SC
    Neuroimage; 2014 Aug; 96():117-32. PubMed ID: 24705202
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Tree-guided sparse coding for brain disease classification.
    Liu M; Zhang D; Yap PT; Shen D
    Med Image Comput Comput Assist Interv; 2012; 15(Pt 3):239-47. PubMed ID: 23286136
    [TBL] [Abstract][Full Text] [Related]  

  • 13. SACICA: a sparse approximation coefficient-based ICA model for functional magnetic resonance imaging data analysis.
    Wang N; Zeng W; Chen L
    J Neurosci Methods; 2013 May; 216(1):49-61. PubMed ID: 23563324
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Unsupervised learning and mapping of active brain functional MRI signals based on hidden semi-Markov event sequence models.
    Faisan S; Thoraval L; Armspach JP; Metz-Lutz MN; Heitz F
    IEEE Trans Med Imaging; 2005 Feb; 24(2):263-76. PubMed ID: 15707252
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Local sparsity enhanced compressed sensing magnetic resonance imaging in uniform discrete curvelet domain.
    Yang B; Yuan M; Ma Y; Zhang J; Zhan K
    BMC Med Imaging; 2015 Aug; 15():28. PubMed ID: 26253135
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Sparse estimation automatically selects voxels relevant for the decoding of fMRI activity patterns.
    Yamashita O; Sato MA; Yoshioka T; Tong F; Kamitani Y
    Neuroimage; 2008 Oct; 42(4):1414-29. PubMed ID: 18598768
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Hyperplane navigation: a method to set individual scores in fMRI group datasets.
    Sato JR; Thomaz CE; Cardoso EF; Fujita A; Martin Mda G; Amaro E
    Neuroimage; 2008 Oct; 42(4):1473-80. PubMed ID: 18644242
    [TBL] [Abstract][Full Text] [Related]  

  • 18. From spatial regularization to anatomical priors in fMRI analysis.
    Ou W; Golland P
    Inf Process Med Imaging; 2005; 19():88-100. PubMed ID: 17354687
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Overlapping replicator dynamics for functional subnetwork identification.
    Yoldemir B; Ng B; Abugharbieh R
    Med Image Comput Comput Assist Interv; 2013; 16(Pt 2):682-9. PubMed ID: 24579200
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Sparse representation of higher-order functional interaction patterns in task-based FMRI data.
    Zhang S; Li X; Lv J; Jiang X; Zhu D; Chen H; Zhang T; Guo L; Liu T
    Med Image Comput Comput Assist Interv; 2013; 16(Pt 3):626-34. PubMed ID: 24505814
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.