BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

674 related articles for article (PubMed ID: 17360198)

  • 1. Modeling state-related fMRI activity using change-point theory.
    Lindquist MA; Waugh C; Wager TD
    Neuroimage; 2007 Apr; 35(3):1125-41. PubMed ID: 17360198
    [TBL] [Abstract][Full Text] [Related]  

  • 2. fMRI bold signal analysis using a novel nonparametric statistical method.
    De Mazière PA; Van Hulle MM
    J Magn Reson; 2007 Mar; 185(1):138-51. PubMed ID: 17196411
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Activation detection in fMRI using a maximum energy ratio statistic obtained by adaptive spatial filtering.
    Hossein-Zadeh GA; Ardekani BA; Soltanian-Zadeh H
    IEEE Trans Med Imaging; 2003 Jul; 22(7):795-805. PubMed ID: 12906234
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Analyzing the connectivity between regions of interest: an approach based on cluster Granger causality for fMRI data analysis.
    Sato JR; Fujita A; Cardoso EF; Thomaz CE; Brammer MJ; Amaro E
    Neuroimage; 2010 Oct; 52(4):1444-55. PubMed ID: 20472076
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Bayesian fMRI data analysis with sparse spatial basis function priors.
    Flandin G; Penny WD
    Neuroimage; 2007 Feb; 34(3):1108-25. PubMed ID: 17157034
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Adaptive denoising of event-related functional magnetic resonance imaging data using spectral subtraction.
    Kadah YM
    IEEE Trans Biomed Eng; 2004 Nov; 51(11):1944-53. PubMed ID: 15536896
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Model-independent method for fMRI analysis.
    Soltanian-Zadeh H; Peck DJ; Hearshen DO; Lajiness-O'Neill RR
    IEEE Trans Med Imaging; 2004 Mar; 23(3):285-96. PubMed ID: 15027521
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Hidden Markov event sequence models: toward unsupervised functional MRI brain mapping.
    Faisan S; Thoraval L; Armspach JP; Foucher JR; Metz-Lutz MN; Heitz F
    Acad Radiol; 2005 Jan; 12(1):25-36. PubMed ID: 15691723
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Development and validation of retrospective spinal cord motion time-course estimates (RESPITE) for spin-echo spinal fMRI: Improved sensitivity and specificity by means of a motion-compensating general linear model analysis.
    Figley CR; Stroman PW
    Neuroimage; 2009 Jan; 44(2):421-7. PubMed ID: 18835581
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Fully Bayesian spatio-temporal modeling of FMRI data.
    Woolrich MW; Jenkinson M; Brady JM; Smith SM
    IEEE Trans Med Imaging; 2004 Feb; 23(2):213-31. PubMed ID: 14964566
    [TBL] [Abstract][Full Text] [Related]  

  • 11. fMRI data analysis with nonstationary noise models: a Bayesian approach.
    Luo H; Puthusserypady S
    IEEE Trans Biomed Eng; 2007 Sep; 54(9):1621-30. PubMed ID: 17867354
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A group model for stable multi-subject ICA on fMRI datasets.
    Varoquaux G; Sadaghiani S; Pinel P; Kleinschmidt A; Poline JB; Thirion B
    Neuroimage; 2010 May; 51(1):288-99. PubMed ID: 20153834
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Using ICA and realistic BOLD models to obtain joint EEG/fMRI solutions to the problem of source localization.
    Brookings T; Ortigue S; Grafton S; Carlson J
    Neuroimage; 2009 Jan; 44(2):411-20. PubMed ID: 18845263
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Model-free fMRI group analysis using FENICA.
    Schöpf V; Windischberger C; Robinson S; Kasess CH; Fischmeister FP; Lanzenberger R; Albrecht J; Kleemann AM; Kopietz R; Wiesmann M; Moser E
    Neuroimage; 2011 Mar; 55(1):185-93. PubMed ID: 21078400
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Analysis of FMRI data with drift: modified general linear model and Bayesian estimator.
    Luo H; Puthusserypady S
    IEEE Trans Biomed Eng; 2008 May; 55(5):1504-11. PubMed ID: 18440896
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Empirical Markov Chain Monte Carlo Bayesian analysis of fMRI data.
    de Pasquale F; Del Gratta C; Romani GL
    Neuroimage; 2008 Aug; 42(1):99-111. PubMed ID: 18538586
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A comment on the severity of the effects of non-white noise in fMRI time-series.
    Smith AT; Singh KD; Balsters JH
    Neuroimage; 2007 Jun; 36(2):282-8. PubMed ID: 17098446
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Integrated MEG/EEG and fMRI model based on neural masses.
    Babajani A; Soltanian-Zadeh H
    IEEE Trans Biomed Eng; 2006 Sep; 53(9):1794-801. PubMed ID: 16941835
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A least angle regression method for fMRI activation detection in phase-encoded experimental designs.
    Li X; Coyle D; Maguire L; McGinnity TM; Watson DR; Benali H
    Neuroimage; 2010 Oct; 52(4):1390-400. PubMed ID: 20472078
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 34.