Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images
White matter hyperintensities (WMHs) have been associated with various cerebrovascular and neurodegenerative diseases. Reliable quantification of WMHs is essential for understanding their clinical impact in normal and pathological populations. Automated segmentation of WMHs is highly challenging due...
Autors principals: | Sundaresan, V, Zamboni, G, Rothwell, PM, Jenkinson, M, Griffanti, L |
---|---|
Format: | Journal article |
Idioma: | English |
Publicat: |
Elsevier
2021
|
Ítems similars
-
Brain tumour segmentation using a triplanar ensemble of U-Nets on MR images
per: Sundaresan, V, et al.
Publicat: (2021) -
Comparison of domain adaptation techniques for white matter hyperintensity segmentation in brain MR images
per: Sundaresan, V, et al.
Publicat: (2021) -
Omni-supervised domain adversarial training for white matter hyperintensity segmentation in the UK Biobank
per: Sundaresan, V, et al.
Publicat: (2022) -
Modelling the distribution of white matter hyperintensities due to ageing on MRI images using Bayesian inference
per: Sundaresan, V, et al.
Publicat: (2018) -
BIANCA (Brain Intensity AbNormality Classification Algorithm): A new tool for automated segmentation of white matter hyperintensities
per: Griffanti, L, et al.
Publicat: (2016)