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 *

2732 related articles for article (PubMed ID: 18501637)

  • 1. Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference.
    Smith SM; Nichols TE
    Neuroimage; 2009 Jan; 44(1):83-98. PubMed ID: 18501637
    [TBL] [Abstract][Full Text] [Related]  

  • 2. A sensitive, noise-resistant method for identifying focal demyelination and remyelination in patients with multiple sclerosis via voxel-wise changes in magnetization transfer ratio.
    Dwyer M; Bergsland N; Hussein S; Durfee J; Wack D; Zivadinov R
    J Neurol Sci; 2009 Jul; 282(1-2):86-95. PubMed ID: 19386319
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Enhanced signal detection in neuroimaging by means of regional control of the global false discovery rate.
    Langers DR; Jansen JF; Backes WH
    Neuroimage; 2007 Oct; 38(1):43-56. PubMed ID: 17825583
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Probabilistic TFCE: A generalized combination of cluster size and voxel intensity to increase statistical power.
    Spisák T; Spisák Z; Zunhammer M; Bingel U; Smith S; Nichols T; Kincses T
    Neuroimage; 2019 Jan; 185():12-26. PubMed ID: 30296561
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Detecting activations in PET and fMRI: levels of inference and power.
    Friston KJ; Holmes A; Poline JB; Price CJ; Frith CD
    Neuroimage; 1996 Dec; 4(3 Pt 1):223-35. PubMed ID: 9345513
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Intracranial vessel segmentation from time-of-flight MRA using pre-processing of the MIP Z-buffer: accuracy of the ZBS algorithm.
    Chapman BE; Stapelton JO; Parker DL
    Med Image Anal; 2004 Jun; 8(2):113-26. PubMed ID: 15063861
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Combining voxel intensity and cluster extent with permutation test framework.
    Hayasaka S; Nichols TE
    Neuroimage; 2004 Sep; 23(1):54-63. PubMed ID: 15325352
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Determining the optimal level of smoothing in cortical thickness analysis: a hierarchical approach based on sequential statistical thresholding.
    Bernal-Rusiel JL; Atienza M; Cantero JL
    Neuroimage; 2010 Aug; 52(1):158-71. PubMed ID: 20362677
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluation of thresholding methods for activation likelihood estimation meta-analysis via large-scale simulations.
    Frahm L; Cieslik EC; Hoffstaedter F; Satterthwaite TD; Fox PT; Langner R; Eickhoff SB
    Hum Brain Mapp; 2022 Sep; 43(13):3987-3997. PubMed ID: 35535616
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses.
    Thirion B; Pinel P; Mériaux S; Roche A; Dehaene S; Poline JB
    Neuroimage; 2007 Mar; 35(1):105-20. PubMed ID: 17239619
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Complex threshold method for identifying pixels that contain predominantly noise in magnetic resonance images.
    Pandian DS; Ciulla C; Haacke EM; Jiang J; Ayaz M
    J Magn Reson Imaging; 2008 Sep; 28(3):727-35. PubMed ID: 18777533
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An evaluation of thresholding techniques in fMRI analysis.
    Logan BR; Rowe DB
    Neuroimage; 2004 May; 22(1):95-108. PubMed ID: 15110000
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Adjusting the neuroimaging statistical inferences for nonstationarity.
    Salimi-Khorshidi G; Smith SM; Nichols TE
    Med Image Comput Comput Assist Interv; 2009; 12(Pt 1):992-9. PubMed ID: 20426085
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Comparison of a non-stationary voxelation-corrected cluster-size test with TFCE for group-Level MRI inference.
    Li H; Nickerson LD; Nichols TE; Gao JH
    Hum Brain Mapp; 2017 Mar; 38(3):1269-1280. PubMed ID: 27785843
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An evaluation of spatial thresholding techniques in fMRI analysis.
    Logan BR; Geliazkova MP; Rowe DB
    Hum Brain Mapp; 2008 Dec; 29(12):1379-89. PubMed ID: 18064589
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Measuring fMRI reliability with the intra-class correlation coefficient.
    Caceres A; Hall DL; Zelaya FO; Williams SC; Mehta MA
    Neuroimage; 2009 Apr; 45(3):758-68. PubMed ID: 19166942
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Nonstationary cluster-size inference with random field and permutation methods.
    Hayasaka S; Phan KL; Liberzon I; Worsley KJ; Nichols TE
    Neuroimage; 2004 Jun; 22(2):676-87. PubMed ID: 15193596
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Estimation of false discovery rates for wavelet-denoised statistical parametric maps.
    Srikanth R; Casanova R; Laurienti PJ; Peiffer AM; Maldjian JA
    Neuroimage; 2006 Oct; 33(1):72-84. PubMed ID: 16919480
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Monte-Carlo sure: a black-box optimization of regularization parameters for general denoising algorithms.
    Ramani S; Blu T; Unser M
    IEEE Trans Image Process; 2008 Sep; 17(9):1540-54. PubMed ID: 18701393
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 137.