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Journal Abstract Search

203 related items for PubMed ID: 26518734

  • 1. Automated lesion detection on MRI scans using combined unsupervised and supervised methods.
    Guo D, Fridriksson J, Fillmore P, Rorden C, Yu H, Zheng K, Wang S.
    BMC Med Imaging; 2015 Oct 30; 15():50. PubMed ID: 26518734
    [Abstract] [Full Text] [Related]

  • 2. 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]

  • 3. Automated separation of diffusely abnormal white matter from focal white matter lesions on MRI in multiple sclerosis.
    Maranzano J, Dadar M, Zhernovaia M, Arnold DL, Collins DL, Narayanan S.
    Neuroimage; 2020 Jun 15; 213():116690. PubMed ID: 32119987
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  • 4. RFDCR: Automated brain lesion segmentation using cascaded random forests with dense conditional random fields.
    Chen G, Li Q, Shi F, Rekik I, Pan Z.
    Neuroimage; 2020 May 01; 211():116620. PubMed ID: 32057997
    [Abstract] [Full Text] [Related]

  • 5. Automatic segmentation of white matter hyperintensities: validation and comparison with state-of-the-art methods on both Multiple Sclerosis and elderly subjects.
    Tran P, Thoprakarn U, Gourieux E, Dos Santos CL, Cavedo E, Guizard N, Cotton F, Krolak-Salmon P, Delmaire C, Heidelberg D, Pyatigorskaya N, Ströer S, Dormont D, Martini JB, Chupin M, Alzheimer's Disease Neuroimaging Initiatives, for the Frontotemporal Lobar Degeneration Neuroimaging Initiative.
    Neuroimage Clin; 2022 May 01; 33():102940. PubMed ID: 35051744
    [Abstract] [Full Text] [Related]

  • 6. Limited One-time Sampling Irregularity Map (LOTS-IM) for Automatic Unsupervised Assessment of White Matter Hyperintensities and Multiple Sclerosis Lesions in Structural Brain Magnetic Resonance Images.
    Rachmadi MF, Valdés-Hernández MDC, Li H, Guerrero R, Meijboom R, Wiseman S, Waldman A, Zhang J, Rueckert D, Wardlaw J, Komura T.
    Comput Med Imaging Graph; 2020 Jan 01; 79():101685. PubMed ID: 31846826
    [Abstract] [Full Text] [Related]

  • 7. Supervised and unsupervised methods for prostate cancer segmentation with multispectral MRI.
    Ozer S, Langer DL, Liu X, Haider MA, van der Kwast TH, Evans AJ, Yang Y, Wernick MN, Yetik IS.
    Med Phys; 2010 Apr 01; 37(4):1873-83. PubMed ID: 20443509
    [Abstract] [Full Text] [Related]

  • 8. Extra tree forests for sub-acute ischemic stroke lesion segmentation in MR sequences.
    Maier O, Wilms M, von der Gablentz J, Krämer UM, Münte TF, Handels H.
    J Neurosci Methods; 2015 Jan 30; 240():89-100. PubMed ID: 25448384
    [Abstract] [Full Text] [Related]

  • 9. Tissue Probability Based Registration of Diffusion-Weighted Magnetic Resonance Imaging.
    Malovani C, Friedman N, Ben-Eliezer N, Tavor I.
    J Magn Reson Imaging; 2021 Oct 30; 54(4):1066-1076. PubMed ID: 33894095
    [Abstract] [Full Text] [Related]

  • 10. Co-trained convolutional neural networks for automated detection of prostate cancer in multi-parametric MRI.
    Yang X, Liu C, Wang Z, Yang J, Min HL, Wang L, Cheng KT.
    Med Image Anal; 2017 Dec 30; 42():212-227. PubMed ID: 28850876
    [Abstract] [Full Text] [Related]

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  • 13. Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding.
    Sundaresan V, Zamboni G, Le Heron C, Rothwell PM, Husain M, Battaglini M, De Stefano N, Jenkinson M, Griffanti L.
    Neuroimage; 2019 Nov 15; 202():116056. PubMed ID: 31376518
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  • 16. Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening.
    Alaverdyan Z, Jung J, Bouet R, Lartizien C.
    Med Image Anal; 2020 Feb 15; 60():101618. PubMed ID: 31841950
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  • 18. Automatic segmentation of MR brain images of preterm infants using supervised classification.
    Moeskops P, Benders MJ, Chiţ SM, Kersbergen KJ, Groenendaal F, de Vries LS, Viergever MA, Išgum I.
    Neuroimage; 2015 Sep 15; 118():628-41. PubMed ID: 26057591
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  • 20. Probability distribution function-based classification of structural MRI for the detection of Alzheimer's disease.
    Beheshti I, Demirel H, Alzheimer’s Disease Neuroimaging Initiative.
    Comput Biol Med; 2015 Sep 15; 64():208-16. PubMed ID: 26226415
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