BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

414 related articles for article (PubMed ID: 18055174)

  • 1. A novel method for automatic determination of different stages of multiple sclerosis lesions in brain MR FLAIR images.
    Khayati R; Vafadust M; Towhidkhah F; Nabavi SM
    Comput Med Imaging Graph; 2008 Mar; 32(2):124-33. PubMed ID: 18055174
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Fully automatic segmentation of multiple sclerosis lesions in brain MR FLAIR images using adaptive mixtures method and Markov random field model.
    Khayati R; Vafadust M; Towhidkhah F; Nabavi M
    Comput Biol Med; 2008 Mar; 38(3):379-90. PubMed ID: 18262511
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Relationship between contrast enhancement on fluid-attenuated inversion recovery MR sequences and signal intensity on T2-weighted MR images: visual evaluation of brain tumors.
    Kubota T; Yamada K; Kizu O; Hirota T; Ito H; Ishihara K; Nishimura T
    J Magn Reson Imaging; 2005 Jun; 21(6):694-700. PubMed ID: 15906343
    [TBL] [Abstract][Full Text] [Related]  

  • 4. An approach to comparing accuracies of two FLAIR MR sequences in the detection of multiple sclerosis lesions in the brain in the absence of gold standard.
    Bilello M; Suri N; Krejza J; Woo JH; Bagley LJ; Mamourian AC; Vossough A; Chen JY; Millian BR; Mulderink T; Markowitz CE; Melhem ER
    Acad Radiol; 2010 Jun; 17(6):686-95. PubMed ID: 20457413
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-aided detection of multiple sclerosis lesions in brain magnetic resonance images: False positive reduction scheme consisted of rule-based, level set method, and support vector machine.
    Yamamoto D; Arimura H; Kakeda S; Magome T; Yamashita Y; Toyofuku F; Ohki M; Higashida Y; Korogi Y
    Comput Med Imaging Graph; 2010 Jul; 34(5):404-13. PubMed ID: 20189353
    [TBL] [Abstract][Full Text] [Related]  

  • 6. [Segmentation of multiple sclerosis lesions based on Markov random fields model for MR images].
    Li B; Chen W
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2009 Aug; 26(4):861-5. PubMed ID: 19813627
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Voxel-based iterative sensitivity (VBIS) analysis: methods and a validation of intensity scaling for T2-weighted imaging of hippocampal sclerosis.
    Abbott DF; Pell GS; Pardoe H; Jackson GD
    Neuroimage; 2009 Feb; 44(3):812-9. PubMed ID: 18996207
    [TBL] [Abstract][Full Text] [Related]  

  • 8. T1-weighted fluid-attenuated inversion recovery and T1-weighted fast spin-echo contrast-enhanced imaging: a comparison in 20 patients with brain lesions.
    Al-Saeed O; Ismail M; Athyal RP; Rudwan M; Khafajee S
    J Med Imaging Radiat Oncol; 2009 Aug; 53(4):366-72. PubMed ID: 19695043
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Evaluating intensity normalization on MRIs of human brain with multiple sclerosis.
    Shah M; Xiao Y; Subbanna N; Francis S; Arnold DL; Collins DL; Arbel T
    Med Image Anal; 2011 Apr; 15(2):267-82. PubMed ID: 21233004
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Semiautomatic parametric model-based 3D lesion segmentation for evaluation of MR-guided radiofrequency ablation therapy.
    Lazebnik RS; Weinberg BD; Breen MS; Lewin JS; Wilson DL
    Acad Radiol; 2005 Dec; 12(12):1491-501. PubMed ID: 16321737
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Computer-aided evaluation method of white matter hyperintensities related to subcortical vascular dementia based on magnetic resonance imaging.
    Kawata Y; Arimura H; Yamashita Y; Magome T; Ohki M; Toyofuku F; Higashida Y; Tsuchiya K
    Comput Med Imaging Graph; 2010 Jul; 34(5):370-6. PubMed ID: 20116974
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic segmentation and classification of multiple sclerosis in multichannel MRI.
    Akselrod-Ballin A; Galun M; Gomori JM; Filippi M; Valsasina P; Basri R; Brandt A
    IEEE Trans Biomed Eng; 2009 Oct; 56(10):2461-9. PubMed ID: 19758850
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Probabilistic segmentation of white matter lesions in MR imaging.
    Anbeek P; Vincken KL; van Osch MJ; Bisschops RH; van der Grond J
    Neuroimage; 2004 Mar; 21(3):1037-44. PubMed ID: 15006671
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automated segmentation of multiple sclerosis lesion subtypes with multichannel MRI.
    Wu Y; Warfield SK; Tan IL; Wells WM; Meier DS; van Schijndel RA; Barkhof F; Guttmann CR
    Neuroimage; 2006 Sep; 32(3):1205-15. PubMed ID: 16797188
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Agreement between different input image types in brain atrophy measurement in multiple sclerosis using SIENAX and SIENA.
    Neacsu V; Jasperse B; Korteweg T; Knol DL; Valsasina P; Filippi M; Barkhof F; Rovaris M; Vrenken H;
    J Magn Reson Imaging; 2008 Sep; 28(3):559-65. PubMed ID: 18777529
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Pattern recognition system for the discrimination of multiple sclerosis from cerebral microangiopathy lesions based on texture analysis of magnetic resonance images.
    Theocharakis P; Glotsos D; Kalatzis I; Kostopoulos S; Georgiadis P; Sifaki K; Tsakouridou K; Malamas M; Delibasis G; Cavouras D; Nikiforidis G
    Magn Reson Imaging; 2009 Apr; 27(3):417-22. PubMed ID: 18786795
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Hepatic hemangioma: correlation of enhancement types with diffusion-weighted MR findings and apparent diffusion coefficients.
    Goshima S; Kanematsu M; Kondo H; Yokoyama R; Kajita K; Tsuge Y; Shiratori Y; Onozuka M; Moriyama N
    Eur J Radiol; 2009 May; 70(2):325-30. PubMed ID: 18321673
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Rapid and automatic calculation of the midsagittal plane in magnetic resonance diffusion and perfusion images.
    Nowinski WL; Prakash B; Volkau I; Ananthasubramaniam A; Beauchamp NJ
    Acad Radiol; 2006 May; 13(5):652-63. PubMed ID: 16627207
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automatic detection of gadolinium-enhancing multiple sclerosis lesions in brain MRI using conditional random fields.
    Karimaghaloo Z; Shah M; Francis SJ; Arnold DL; Collins DL; Arbel T
    IEEE Trans Med Imaging; 2012 Jun; 31(6):1181-94. PubMed ID: 22318484
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Adaptive Markov modeling for mutual-information-based, unsupervised MRI brain-tissue classification.
    Awate SP; Tasdizen T; Foster N; Whitaker RT
    Med Image Anal; 2006 Oct; 10(5):726-39. PubMed ID: 16919993
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 21.