Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change.
Cassidy M. FifordCarole H. SudreHugh PembertonPhoebe WalshEmily N. ManningIan B. MaloneJennifer NicholasWillem H. BouvyOwen T. CarmichaelGeert Jan BiesselsM. Jorge CardosoJosephine BarnesPublished in: Neuroinformatics (2020)
Keyphrases
- white matter
- gray matter
- corpus callosum
- cerebrospinal fluid
- grey matter
- magnetic resonance images
- bayesian model selection
- human brain
- diffusion tensor images
- partial volume effects
- fiber bundles
- diffusion tensor
- mri data
- dt mri
- brain mr images
- brain mri
- mr brain images
- diffusion tensor imaging
- medical images
- brain images
- mr images
- model selection
- image segmentation
- segmentation algorithm
- information processing
- em algorithm
- medical imaging
- partial volume
- brain tissue
- brain tumors
- posterior probability
- accurate segmentation
- energy function
- magnetic resonance
- multiscale
- brain structures
- computer vision
- maximum likelihood
- level set
- tensor field
- decision making
- fully automatic