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 *

141 related articles for article (PubMed ID: 19543931)

  • 21. Bayesian reconstruction of multiscale local contrast images from brain activity.
    Song S; Ma X; Zhan Y; Zhan Z; Yao L; Zhang J
    J Neurosci Methods; 2013 Oct; 220(1):39-45. PubMed ID: 23999175
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Multivariate group-level analysis for task fMRI data with canonical correlation analysis.
    Zhuang X; Yang Z; Sreenivasan KR; Mishra VR; Curran T; Nandy R; Cordes D
    Neuroimage; 2019 Jul; 194():25-41. PubMed ID: 30894332
    [TBL] [Abstract][Full Text] [Related]  

  • 23. fMRI-EEG integrated cortical source imaging by use of time-variant spatial constraints.
    Liu Z; He B
    Neuroimage; 2008 Feb; 39(3):1198-214. PubMed ID: 18036833
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Adaptively and spatially estimating the hemodynamic response functions in fMRI.
    Wang J; Zhu H; Fan J; Giovanello K; Lin W
    Med Image Comput Comput Assist Interv; 2011; 14(Pt 2):269-76. PubMed ID: 21995038
    [TBL] [Abstract][Full Text] [Related]  

  • 25. On the characterization of single-event related brain activity from functional Magnetic Resonance Imaging (fMRI) measurements.
    Khoram N; Zayane C; Laleg-Kirati TM; Djellouli R
    Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():2396-9. PubMed ID: 25570472
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Linear systems analysis of the fMRI signal.
    Boynton GM; Engel SA; Heeger DJ
    Neuroimage; 2012 Aug; 62(2):975-84. PubMed ID: 22289807
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A novel approach to activation detection in fMRI based on empirical mode decomposition.
    Zheng T; Cai M; Jiang T
    J Integr Neurosci; 2010 Dec; 9(4):407-27. PubMed ID: 21213412
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Support vector clustering for brain activation detection.
    Wang D; Shi L; Yeung DS; Heng PA; Wong TT; Tsang EC
    Med Image Comput Comput Assist Interv; 2005; 8(Pt 1):572-9. PubMed ID: 16685892
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Optimal HRF and smoothing parameters for fMRI time series within an autoregressive modeling framework.
    Galka A; Siniatchkin M; Stephani U; Groening K; Wolff S; Bosch-Bayard J; Ozaki T
    J Integr Neurosci; 2010 Dec; 9(4):429-52. PubMed ID: 21213413
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Unsupervised robust nonparametric estimation of the hemodynamic response function for any fMRI experiment.
    Ciuciu P; Poline JB; Marrelec G; Idier J; Pallier C; Benali H
    IEEE Trans Med Imaging; 2003 Oct; 22(10):1235-51. PubMed ID: 14552578
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Support vector machine learning-based fMRI data group analysis.
    Wang Z; Childress AR; Wang J; Detre JA
    Neuroimage; 2007 Jul; 36(4):1139-51. PubMed ID: 17524674
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Optimization of functional MRI for detection, decoding and high-resolution imaging of the response patterns of cortical columns.
    Chaimow D; Uğurbil K; Shmuel A
    Neuroimage; 2018 Jan; 164():67-99. PubMed ID: 28461061
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Clustered components analysis for functional MRI.
    Chen S; Bouman CA; Lowe MJ
    IEEE Trans Med Imaging; 2004 Jan; 23(1):85-98. PubMed ID: 14719690
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Sparse geostatistical analysis in clustering fMRI time series.
    Ye J; Lazar NA; Li Y
    J Neurosci Methods; 2011 Aug; 199(2):336-45. PubMed ID: 21641934
    [TBL] [Abstract][Full Text] [Related]  

  • 35. A family of locally constrained CCA models for detecting activation patterns in fMRI.
    Zhuang X; Yang Z; Curran T; Byrd R; Nandy R; Cordes D
    Neuroimage; 2017 Apr; 149():63-84. PubMed ID: 28041980
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Recursive approach of EEG-segment-based principal component analysis substantially reduces cryogenic pump artifacts in simultaneous EEG-fMRI data.
    Kim HC; Yoo SS; Lee JH
    Neuroimage; 2015 Jan; 104():437-51. PubMed ID: 25284302
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Multi-subject brain decoding with multi-task feature selection.
    Wang L; Tang X; Liu W; Peng Y; Gao T; Xu Y
    Biomed Mater Eng; 2014; 24(6):2987-94. PubMed ID: 25227006
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Combining multivariate voxel selection and support vector machines for mapping and classification of fMRI spatial patterns.
    De Martino F; Valente G; Staeren N; Ashburner J; Goebel R; Formisano E
    Neuroimage; 2008 Oct; 43(1):44-58. PubMed ID: 18672070
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Feature characterization in fMRI data: the Information Bottleneck approach.
    Thirion B; Faugeras O
    Med Image Anal; 2004 Dec; 8(4):403-19. PubMed ID: 15567705
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Visual feature extraction from voxel-weighted averaging of stimulus images in 2 fMRI studies.
    Hart CB; Rose WJ
    IEEE Trans Biomed Eng; 2013 Nov; 60(11):3124-30. PubMed ID: 23782790
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.