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Journal Abstract Search

95 related items for PubMed ID: 23613032

  • 1. Temporally consistent probabilistic detection of new multiple sclerosis lesions in brain MRI.
    Elliott C, Arnold DL, Collins DL, Arbel T.
    IEEE Trans Med Imaging; 2013 Aug; 32(8):1490-503. PubMed ID: 23613032
    [Abstract] [Full Text] [Related]

  • 2. 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
    [Abstract] [Full Text] [Related]

  • 3. 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
    [Abstract] [Full Text] [Related]

  • 4. 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
    [Abstract] [Full Text] [Related]

  • 5. 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
    [Abstract] [Full Text] [Related]

  • 6. 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
    [Abstract] [Full Text] [Related]

  • 7. Bayesian classification of multiple sclerosis lesions in longitudinal MRI using subtraction images.
    Elliott C, Francis SJ, Arnold DL, Collins DL, Arbel T.
    Med Image Comput Comput Assist Interv; 2010 Oct; 13(Pt 2):290-7. PubMed ID: 20879327
    [Abstract] [Full Text] [Related]

  • 8. White matter lesion extension to automatic brain tissue segmentation on MRI.
    de Boer R, Vrooman HA, van der Lijn F, Vernooij MW, Ikram MA, van der Lugt A, Breteler MM, Niessen WJ.
    Neuroimage; 2009 May 01; 45(4):1151-61. PubMed ID: 19344687
    [Abstract] [Full Text] [Related]

  • 9. Spatial decision forests for MS lesion segmentation in multi-channel magnetic resonance images.
    Geremia E, Clatz O, Menze BH, Konukoglu E, Criminisi A, Ayache N.
    Neuroimage; 2011 Jul 15; 57(2):378-90. PubMed ID: 21497655
    [Abstract] [Full Text] [Related]

  • 10. Temporal Hierarchical Adaptive Texture CRF for Automatic Detection of Gadolinium-Enhancing Multiple Sclerosis Lesions in Brain MRI.
    Karimaghaloo Z, Rivaz H, Arnold DL, Collins DL, Arbel T.
    IEEE Trans Med Imaging; 2015 Jun 15; 34(6):1227-41. PubMed ID: 25532171
    [Abstract] [Full Text] [Related]

  • 11. 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 15; 32(2):124-33. PubMed ID: 18055174
    [Abstract] [Full Text] [Related]

  • 12. 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 15; 34(5):404-13. PubMed ID: 20189353
    [Abstract] [Full Text] [Related]

  • 13. [Approaches to segment multiple-sclerosis lesions on conventional brain MRI].
    Souplet JC, Lebrun C, Chanalet S, Ayache N, Malandain G.
    Rev Neurol (Paris); 2009 Jan 15; 165(1):7-14. PubMed ID: 18808780
    [Abstract] [Full Text] [Related]

  • 14. MRI texture analysis in multiple sclerosis: toward a clinical analysis protocol.
    Harrison LC, Raunio M, Holli KK, Luukkaala T, Savio S, Elovaara I, Soimakallio S, Eskola HJ, Dastidar P.
    Acad Radiol; 2010 Jun 15; 17(6):696-707. PubMed ID: 20457414
    [Abstract] [Full Text] [Related]

  • 15. Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans.
    Griffis JC, Allendorfer JB, Szaflarski JP.
    J Neurosci Methods; 2016 Jan 15; 257():97-108. PubMed ID: 26432931
    [Abstract] [Full Text] [Related]

  • 16. Validation of White-Matter Lesion Change Detection Methods on a Novel Publicly Available MRI Image Database.
    Lesjak Ž, Pernuš F, Likar B, Špiclin Ž.
    Neuroinformatics; 2016 Oct 15; 14(4):403-20. PubMed ID: 27207310
    [Abstract] [Full Text] [Related]

  • 17. [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 15; 26(4):861-5. PubMed ID: 19813627
    [Abstract] [Full Text] [Related]

  • 18. Evaluation of accuracy in MS lesion volumetry using realistic lesion phantoms.
    Rexilius J, Hahn HK, Schlüter M, Bourquain H, Peitgen HO.
    Acad Radiol; 2005 Jan 15; 12(1):17-24. PubMed ID: 15691722
    [Abstract] [Full Text] [Related]

  • 19. Twenty new digital brain phantoms for creation of validation image data bases.
    Aubert-Broche B, Griffin M, Pike GB, Evans AC, Collins DL.
    IEEE Trans Med Imaging; 2006 Nov 15; 25(11):1410-6. PubMed ID: 17117770
    [Abstract] [Full Text] [Related]

  • 20. 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 15; 32(3):1205-15. PubMed ID: 16797188
    [Abstract] [Full Text] [Related]

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