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Journal Abstract Search

304 related items for PubMed ID: 27254085

  • 1. The effects of white matter disease on the accuracy of automated segmentation.
    Karim HT, Andreescu C, MacCloud RL, Butters MA, Reynolds CF, Aizenstein HJ, Tudorascu DL.
    Psychiatry Res Neuroimaging; 2016 Jul 30; 253():7-14. PubMed ID: 27254085
    [Abstract] [Full Text] [Related]

  • 2. UBO Detector - A cluster-based, fully automated pipeline for extracting white matter hyperintensities.
    Jiang J, Liu T, Zhu W, Koncz R, Liu H, Lee T, Sachdev PS, Wen W.
    Neuroimage; 2018 Jul 01; 174():539-549. PubMed ID: 29578029
    [Abstract] [Full Text] [Related]

  • 3. Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI.
    Moeskops P, de Bresser J, Kuijf HJ, Mendrik AM, Biessels GJ, Pluim JPW, Išgum I.
    Neuroimage Clin; 2018 Jul 01; 17():251-262. PubMed ID: 29159042
    [Abstract] [Full Text] [Related]

  • 4. 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 Jul 01; 33():102940. PubMed ID: 35051744
    [Abstract] [Full Text] [Related]

  • 5. Segmentation of white matter hyperintensities using convolutional neural networks with global spatial information in routine clinical brain MRI with none or mild vascular pathology.
    Rachmadi MF, Valdés-Hernández MDC, Agan MLF, Di Perri C, Komura T, Alzheimer's Disease Neuroimaging Initiative.
    Comput Med Imaging Graph; 2018 Jun 01; 66():28-43. PubMed ID: 29523002
    [Abstract] [Full Text] [Related]

  • 6. Improved Automatic Segmentation of White Matter Hyperintensities in MRI Based on Multilevel Lesion Features.
    Rincón M, Díaz-López E, Selnes P, Vegge K, Altmann M, Fladby T, Bjørnerud A.
    Neuroinformatics; 2017 Jul 01; 15(3):231-245. PubMed ID: 28378263
    [Abstract] [Full Text] [Related]

  • 7. Reproducible segmentation of white matter hyperintensities using a new statistical definition.
    Damangir S, Westman E, Simmons A, Vrenken H, Wahlund LO, Spulber G.
    MAGMA; 2017 Jun 01; 30(3):227-237. PubMed ID: 27943055
    [Abstract] [Full Text] [Related]

  • 8. Accuracy and reproducibility of automated white matter hyperintensities segmentation with lesion segmentation tool: A European multi-site 3T study.
    Ribaldi F, Altomare D, Jovicich J, Ferrari C, Picco A, Pizzini FB, Soricelli A, Mega A, Ferretti A, Drevelegas A, Bosch B, Müller BW, Marra C, Cavaliere C, Bartrés-Faz D, Nobili F, Alessandrini F, Barkhof F, Gros-Dagnac H, Ranjeva JP, Wiltfang J, Kuijer J, Sein J, Hoffmann KT, Roccatagliata L, Parnetti L, Tsolaki M, Constantinidis M, Aiello M, Salvatore M, Montalti M, Caulo M, Didic M, Bargallo N, Blin O, Rossini PM, Schonknecht P, Floridi P, Payoux P, Visser PJ, Bordet R, Lopes R, Tarducci R, Bombois S, Hensch T, Fiedler U, Richardson JC, Frisoni GB, Marizzoni M.
    Magn Reson Imaging; 2021 Feb 01; 76():108-115. PubMed ID: 33220450
    [Abstract] [Full Text] [Related]

  • 9. Quantitative MRI of cerebral white matter hyperintensities: A new approach towards understanding the underlying pathology.
    Iordanishvili E, Schall M, Loução R, Zimmermann M, Kotetishvili K, Shah NJ, Oros-Peusquens AM.
    Neuroimage; 2019 Nov 15; 202():116077. PubMed ID: 31398433
    [Abstract] [Full Text] [Related]

  • 10. Validation and Optimization of BIANCA for the Segmentation of Extensive White Matter Hyperintensities.
    Ling Y, Jouvent E, Cousyn L, Chabriat H, De Guio F.
    Neuroinformatics; 2018 Apr 15; 16(2):269-281. PubMed ID: 29594711
    [Abstract] [Full Text] [Related]

  • 11. 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 15; 79():101685. PubMed ID: 31846826
    [Abstract] [Full Text] [Related]

  • 12. Automatic segmentation and quantitative analysis of white matter hyperintensities on FLAIR images using trimmed-likelihood estimator.
    Wang R, Li C, Wang J, Wei X, Li Y, Hui C, Zhu Y, Zhang S.
    Acad Radiol; 2014 Dec 15; 21(12):1512-23. PubMed ID: 25176451
    [Abstract] [Full Text] [Related]

  • 13. End-to-end volumetric segmentation of white matter hyperintensities using deep learning.
    Farkhani S, Demnitz N, Boraxbekk CJ, Lundell H, Siebner HR, Petersen ET, Madsen KH.
    Comput Methods Programs Biomed; 2024 Mar 15; 245():108008. PubMed ID: 38290291
    [Abstract] [Full Text] [Related]

  • 14. Metric to quantify white matter damage on brain magnetic resonance images.
    Valdés Hernández MDC, Chappell FM, Muñoz Maniega S, Dickie DA, Royle NA, Morris Z, Anblagan D, Sakka E, Armitage PA, Bastin ME, Deary IJ, Wardlaw JM.
    Neuroradiology; 2017 Oct 15; 59(10):951-962. PubMed ID: 28815362
    [Abstract] [Full Text] [Related]

  • 15. BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities.
    Griffanti L, Zamboni G, Khan A, Li L, Bonifacio G, Sundaresan V, Schulz UG, Kuker W, Battaglini M, Rothwell PM, Jenkinson M.
    Neuroimage; 2016 Nov 01; 141():191-205. PubMed ID: 27402600
    [Abstract] [Full Text] [Related]

  • 16. White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks.
    Guerrero R, Qin C, Oktay O, Bowles C, Chen L, Joules R, Wolz R, Valdés-Hernández MC, Dickie DA, Wardlaw J, Rueckert D.
    Neuroimage Clin; 2018 Nov 01; 17():918-934. PubMed ID: 29527496
    [Abstract] [Full Text] [Related]

  • 17. Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review.
    Caligiuri ME, Perrotta P, Augimeri A, Rocca F, Quattrone A, Cherubini A.
    Neuroinformatics; 2015 Jul 01; 13(3):261-76. PubMed ID: 25649877
    [Abstract] [Full Text] [Related]

  • 18. Coarse Classification to Region-Scalable Refining for White Matter Lesions Segmentation in Multi-Channel MRI.
    Yu R, Xiao L, Wei Z.
    CNS Neurol Disord Drug Targets; 2017 Jul 01; 16(2):150-159. PubMed ID: 28000558
    [Abstract] [Full Text] [Related]

  • 19. A joint ventricle and WMH segmentation from MRI for evaluation of healthy and pathological changes in the aging brain.
    Atlason HE, Love A, Robertsson V, Blitz AM, Sigurdsson S, Gudnason V, Ellingsen LM.
    PLoS One; 2022 Jul 01; 17(9):e0274212. PubMed ID: 36067136
    [Abstract] [Full Text] [Related]

  • 20. An improved algorithm of white matter hyperintensity detection in elderly adults.
    Ding T, Cohen AD, O'Connor EE, Karim HT, Crainiceanu A, Muschelli J, Lopez O, Klunk WE, Aizenstein HJ, Krafty R, Crainiceanu CM, Tudorascu DL.
    Neuroimage Clin; 2020 Jul 01; 25():102151. PubMed ID: 31927502
    [Abstract] [Full Text] [Related]

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