BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

112 related articles for article (PubMed ID: 15723395)

  • 1. Advantages of frequency-domain modeling in dynamic-susceptibility contrast magnetic resonance cerebral blood flow quantification.
    Chen JJ; Smith MR; Frayne R
    Magn Reson Med; 2005 Mar; 53(3):700-7. PubMed ID: 15723395
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Cerebral blood flow estimation from perfusion-weighted MRI using FT-based MMSE filtering method.
    Sakoglu U; Sood R
    Magn Reson Imaging; 2008 Apr; 26(3):313-22. PubMed ID: 18158225
    [TBL] [Abstract][Full Text] [Related]  

  • 3. A control point interpolation method for the non-parametric quantification of cerebral haemodynamics from dynamic susceptibility contrast MRI.
    Mehndiratta A; MacIntosh BJ; Crane DE; Payne SJ; Chappell MA
    Neuroimage; 2013 Jan; 64():560-70. PubMed ID: 22975158
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies.
    Salluzzi M; Frayne R; Smith MR
    Magn Reson Imaging; 2005 Apr; 23(3):481-92. PubMed ID: 15862650
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Removing the effect of SVD algorithmic artifacts present in quantitative MR perfusion studies.
    Smith MR; Lu H; Trochet S; Frayne R
    Magn Reson Med; 2004 Mar; 51(3):631-4. PubMed ID: 15004809
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Autoregressive moving average (ARMA) model applied to quantification of cerebral blood flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging.
    Murase K; Yamazaki Y; Shinohara M
    Magn Reson Med Sci; 2003 Jul; 2(2):85-95. PubMed ID: 16210825
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Deconvolution with simple extrapolation for improved cerebral blood flow measurement in dynamic susceptibility contrast magnetic resonance imaging during acute ischemic stroke.
    MacDonald ME; Smith MR; Frayne R
    Magn Reson Imaging; 2011 Jun; 29(5):620-9. PubMed ID: 21546188
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Tracer delay correction of cerebral blood flow with dynamic susceptibility contrast-enhanced MRI.
    Ibaraki M; Shimosegawa E; Toyoshima H; Takahashi K; Miura S; Kanno I
    J Cereb Blood Flow Metab; 2005 Mar; 25(3):378-90. PubMed ID: 15674238
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Reassessing the clinical efficacy of two MR quantitative DSC PWI CBF algorithms following cross-calibration with PET images.
    Chen JJ; Frayne R; Smith MR
    Phys Med Biol; 2005 Mar; 50(6):1251-63. PubMed ID: 15798320
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Perfusion quantification using Gaussian process deconvolution.
    Andersen IK; Szymkowiak A; Rasmussen CE; Hanson LG; Marstrand JR; Larsson HB; Hansen LK
    Magn Reson Med; 2002 Aug; 48(2):351-61. PubMed ID: 12210944
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Deconvolution analysis of dynamic contrast-enhanced data based on singular value decomposition optimized by generalized cross validation.
    Murase K; Yamazaki Y; Miyazaki S
    Magn Reson Med Sci; 2004; 3(4):165-75. PubMed ID: 16093635
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Improved residue function and reduced flow dependence in MR perfusion using least-absolute-deviation regularization.
    Wong KK; Tam CP; Ng M; Wong ST; Young GS
    Magn Reson Med; 2009 Feb; 61(2):418-28. PubMed ID: 19161133
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Assessment of clinical data of nonlinear stochastic deconvolution versus block-circulant singular value decomposition for quantitative dynamic susceptibility contrast magnetic resonance imaging.
    Peruzzo D; Zanderigo F; Bertoldo A; Pillonetto G; Cosottini M; Cobelli C
    Magn Reson Imaging; 2011 Sep; 29(7):927-36. PubMed ID: 21616625
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Perfusion quantification by model-free arterial spin labeling using nonlinear stochastic regularization deconvolution.
    Ahlgren A; Wirestam R; Petersen ET; Ståhlberg F; Knutsson L
    Magn Reson Med; 2013 Nov; 70(5):1470-80. PubMed ID: 23281031
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Signal-to-noise ratio effects in quantitative cerebral perfusion using dynamic susceptibility contrast agents.
    Smith MR; Lu H; Frayne R
    Magn Reson Med; 2003 Jan; 49(1):122-8. PubMed ID: 12509827
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Accuracy of deconvolution analysis based on singular value decomposition for quantification of cerebral blood flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging.
    Murase K; Shinohara M; Yamazaki Y
    Phys Med Biol; 2001 Dec; 46(12):3147-59. PubMed ID: 11768497
    [TBL] [Abstract][Full Text] [Related]  

  • 17. DSC perfusion MRI-Quantification and reduction of systematic errors arising in areas of reduced cerebral blood flow.
    Carpenter TK; Armitage PA; Bastin ME; Wardlaw JM
    Magn Reson Med; 2006 Jun; 55(6):1342-9. PubMed ID: 16683256
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Wavelet-based noise reduction for improved deconvolution of time-series data in dynamic susceptibility-contrast MRI.
    Wirestam R; Ståhlberg F
    MAGMA; 2005 Jul; 18(3):113-8. PubMed ID: 15887036
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Quantification of bolus-tracking MRI: Improved characterization of the tissue residue function using Tikhonov regularization.
    Calamante F; Gadian DG; Connelly A
    Magn Reson Med; 2003 Dec; 50(6):1237-47. PubMed ID: 14648572
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Applying the transient error reconstruction algorithm in the assessment of the cerebral blood flow.
    Salluzzi M; Smith MR; Frayne R
    Conf Proc IEEE Eng Med Biol Soc; 2004; 2004():1092-5. PubMed ID: 17271873
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.