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Journal Abstract Search

505 related items for PubMed ID: 31918065

  • 1. A fully convolutional neural network for new T2-w lesion detection in multiple sclerosis.
    Salem M, Valverde S, Cabezas M, Pareto D, Oliver A, Salvi J, Rovira À, Lladó X.
    Neuroimage Clin; 2020; 25():102149. PubMed ID: 31918065
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  • 2. A supervised framework with intensity subtraction and deformation field features for the detection of new T2-w lesions in multiple sclerosis.
    Salem M, Cabezas M, Valverde S, Pareto D, Oliver A, Salvi J, Rovira À, Lladó X.
    Neuroimage Clin; 2018; 17():607-615. PubMed ID: 29234597
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  • 3. Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning.
    Narayana PA, Coronado I, Sujit SJ, Sun X, Wolinsky JS, Gabr RE.
    Magn Reson Imaging; 2020 Jan; 65():8-14. PubMed ID: 31670238
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  • 7. Neuro-fuzzy patch-wise R-CNN for multiple sclerosis segmentation.
    Essa E, Aldesouky D, Hussein SE, Rashad MZ.
    Med Biol Eng Comput; 2020 Sep; 58(9):2161-2175. PubMed ID: 32681214
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  • 9. 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; 79():101685. PubMed ID: 31846826
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  • 10. Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging.
    Duong MT, Rudie JD, Wang J, Xie L, Mohan S, Gee JC, Rauschecker AM.
    AJNR Am J Neuroradiol; 2019 Aug; 40(8):1282-1290. PubMed ID: 31345943
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  • 12. A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images.
    Xue Y, Farhat FG, Boukrina O, Barrett AM, Binder JR, Roshan UW, Graves WW.
    Neuroimage Clin; 2020 Aug; 25():102118. PubMed ID: 31865021
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  • 13. Joint MRI T1 Unenhancing and Contrast-enhancing Multiple Sclerosis Lesion Segmentation with Deep Learning in OPERA Trials.
    Krishnan AP, Song Z, Clayton D, Gaetano L, Jia X, de Crespigny A, Bengtsson T, Carano RAD.
    Radiology; 2022 Mar; 302(3):662-673. PubMed ID: 34904871
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  • 16. Delve into Multiple Sclerosis (MS) lesion exploration: A modified attention U-Net for MS lesion segmentation in Brain MRI.
    Hashemi M, Akhbari M, Jutten C.
    Comput Biol Med; 2022 Jun; 145():105402. PubMed ID: 35344864
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  • 17. Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence.
    McKinley R, Wepfer R, Grunder L, Aschwanden F, Fischer T, Friedli C, Muri R, Rummel C, Verma R, Weisstanner C, Wiestler B, Berger C, Eichinger P, Muhlau M, Reyes M, Salmen A, Chan A, Wiest R, Wagner F.
    Neuroimage Clin; 2020 Jun; 25():102104. PubMed ID: 31927500
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  • 18. Improved Detection of New MS Lesions during Follow-Up Using an Automated MR Coregistration-Fusion Method.
    Galletto Pregliasco A, Collin A, Guéguen A, Metten MA, Aboab J, Deschamps R, Gout O, Duron L, Sadik JC, Savatovsky J, Lecler A.
    AJNR Am J Neuroradiol; 2018 Jul; 39(7):1226-1232. PubMed ID: 29880479
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