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References from Segmentation of white matter lesions in multicentre FLAIR MRI. Local targets link to admitted publications; unresolved targets remain external evidence.
Unresolved reference
2021 · External reference
Fully automatic segmentation of white matter hyperintensities in MR images of the elderly
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10.1007/s10278-017-9983-4 · 2017 · External reference
White matter hyperintensities in vascular contributions to cognitive impairment and dementia (VCID): knowledge gaps and opportunities
10.1016/j.trci.2019.02.001 · 2019 · External reference
Probabilistic segmentation of white matter lesions in MR imaging
10.1016/j.neuroimage.2003.10.012 · 2004 · External reference
Fluid-attenuated inversion recovery vascular hyperintensities: an important imaging marker for cerebrovascular disease
10.3174/ajnr.a2265 · 2011 · External reference
Cerebrovascular pathology in Alzheimer's disease: hopes and gaps
10.1016/j.pscychresns.2020.111184 · 2020 · External reference
Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review
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Automatic detection of white matter hyperintensities in healthy aging and pathology using magnetic resonance imaging: a review
10.1007/s12021-015-9260-y · 2015 · External reference
The comprehensive assessment of neurodegeneration and dementia: Canadian cohort study
10.1017/cjn.2019.27 · 2019 · External reference
Performance comparison of 10 different classification techniques in segmenting white matter hyperintensities in aging
10.1016/j.neuroimage.2017.06.009 · 2017 · External reference
White matter lesion extension to automatic brain tissue segmentation on MRI
10.1016/j.neuroimage.2009.01.011 · 2009 · External reference
Performance of five research-domain automated WM lesion segmentation methods in a multi-center MS study
10.1016/j.neuroimage.2017.09.011 · 2017 · External reference
The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis
2010 · External reference
Brain extraction methods for neurological FLAIR MRI
2018 · External reference
10.1016/j.ynirp.2021.100006 · 2021 · Admitted local publication
Unresolved reference
2018 · External reference
The importance of skip connections in biomedical image segmentation
2016 · External reference
Convolutional neural network for automated FLAIR lesion segmentation on clinical brain MR imaging
10.3174/ajnr.a6138 · 2019 · External reference
Pathologic correlates of incidental MRI white matter signal hyperintensities
10.1212/wnl.43.9.1683 · 1993 · External reference
Characterization of white matter hyperintensities in large-scale MRI-studies
10.3389/fneur.2019.00238 · 2019 · External reference
Review of automatic segmentation methods of multiple sclerosis white matter lesions on conventional magnetic resonance imaging
10.1016/j.media.2012.09.004 · 2013 · External reference
Vascular contributions to cognitive impairment and dementia: a statement for healthcare professionals from the American Heart Association/American Stroke Association
10.1161/str.0b013e3182299496 · 2011 · External reference
BIANCA (Brain Intensity AbNormality Classification Algorithm): a new tool for automated segmentation of white matter hyperintensities
10.1016/j.neuroimage.2016.07.018 · 2016 · External reference
White matter hyperintensity and stroke lesion segmentation and differentiation using convolutional neural networks
10.1016/j.nicl.2017.12.022 · 2018 · External reference
Deep residual learning for image recognition
2016 · External reference
October). Identity mappings in deep residual networks
2016 · External reference
Performance of five automated white matter hyperintensity segmentation methods in a multicenter dataset
10.1038/s41598-019-52966-0 · 2019 · External reference
Densely connected convolutional networks
2017 · External reference
3D U-Net for skull stripping in brain MRI
10.3390/app9030569 · 2019 · External reference
MultiResUNet: rethinking the U-Net architecture for multimodal biomedical image segmentation
10.1016/j.neunet.2019.08.025 · 2020 · External reference
Unresolved reference
2015 · External reference
FLAIR histogram segmentation for measurement of leukoaraiosis volume
10.1002/jmri.10011 · 2001 · External reference
The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods
10.1002/jmri.21049 · 2008 · External reference
The one hundred layers tiramisu: fully convolutional densenets for semantic segmentation
2017 · External reference
Unresolved reference
2020 · External reference
Multiscale denoising and PVA estimation for WML segmentation in FLAIR MRI
2015 · External reference
Robust white matter lesion segmentation in FLAIR MRI
10.1109/tbme.2011.2181167 · 2011 · External reference
Generalized method for partial volume estimation and tissue segmentation in cerebral magnetic resonance images
10.1117/1.jmi.1.1.014002 · 2014 · External reference
Whole volume brain extraction for multi-centre, multi-disease FLAIR MRI datasets
10.1016/j.mri.2019.08.022 · 2020 · External reference
Voxel-wise logistic regression and leave-one-source-out cross validation for white matter hyperintensity segmentation
10.1016/j.mri.2018.06.009 · 2018 · External reference
10.1016/j.jcm.2016.02.012 · 2016 · Admitted local publication
Standardized assessment of automatic segmentation of white matter hyperintensities and results of the WMH segmentation challenge
10.1109/tmi.2019.2905770 · 2019 · External reference
Computer-assisted segmentation of white matter lesions in 3D MR images using support vector machine
10.1016/j.acra.2007.10.012 · 2008 · External reference
Fully convolutional network ensembles for white matter hyperintensities segmentation in MR images
10.1016/j.neuroimage.2018.07.005 · 2018 · External reference
H-DenseUNet: hybrid densely connected UNet for liver and tumor segmentation from CT volumes
10.1109/tmi.2018.2845918 · 2018 · External reference
Unresolved reference
External reference
Neural network generalization: the impact of camera parameters
10.1109/access.2020.2965089 · 2020 · External reference
Fully convolutional networks for semantic segmentation
2015 · External reference
Silver Standard Masks for Data Augmentation Applied to Deep-Learning-Based Skull-Stripping
2018 · External reference
Unresolved reference
2021 · External reference
Leukoaraiosis–new concepts and modern imaging
10.5114/pjr.2018.74344 · 2018 · External reference
Evaluation of a deep learning approach for the segmentation of brain tissues and white matter hyperintensities of presumed vascular origin in MRI
10.1016/j.nicl.2017.10.007 · 2018 · External reference
National neuroinformatics framework for canadian consortium on neurodegeneration in aging (CCNA)
10.3389/fninf.2018.00085 · 2018 · External reference
Are multi-contrast magnetic resonance images necessary for segmenting multiple sclerosis brains? A large cohort study based on deep learning
10.1016/j.mri.2019.10.003 · 2020 · External reference
Unresolved reference
External reference
Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons
10.1177/0962280214537390 · 2015 · External reference
Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges
10.1016/s1474-4422(10)70104-6 · 2010 · External reference
Pathogenesis of leukoaraiosis: a review
10.1161/01.str.28.3.652 · 1997 · External reference
Pathology-preserving intensity standardization framework for multi-institutional FLAIR MRI datasets
10.1016/j.mri.2019.05.001 · 2019 · External reference
October). U-net: convolutional networks for biomedical image segmentation
2015 · External reference
The effect of image resolution on deep learning in radiography
2020 · External reference
Unresolved reference
2017 · External reference
Lesion identification using unified segmentation-normalisation models and fuzzy clustering
10.1016/j.neuroimage.2008.03.028 · 2008 · External reference
Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images
10.1016/j.mri.2012.12.004 · 2013 · External reference
Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration
2019 · External reference
Feature space analysis: effects of MRI protocols
10.1118/1.1414306 · 2001 · External reference
Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations
2017 · External reference
Metrology standards for quantitative imaging biomarkers
10.1148/radiol.2015142202 · 2015 · External reference
Rethinking the inception architecture for computer vision
2016 · External reference
Atherosclerosis imaging and the Canadian atherosclerosis imaging network
2013 · External reference
Unresolved reference
2020 · External reference
Comparison and validation of seven white matter hyperintensities segmentation software in elderly patients
10.1016/j.nicl.2020.102357 · 2020 · External reference
Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration
10.1016/s1474-4422(13)70124-8 · 2013 · External reference
What are white matter hyperintensities made of? Relevance to vascular cognitive impairment
10.1161/jaha.114.001140 · 2015 · External reference
Skip connection U-Net for white matter hyperintensities segmentation from MRI
10.1109/access.2019.2948476 · 2019 · External reference
User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability
10.1016/j.neuroimage.2006.01.015 · 2006 · External reference
Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study
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2012 · External reference
