Random forest active learning for AAA thrombus segmentation in computed tomography angiography images.
Josu MaioraBorja AyerdiManuel GrañaPublished in: Neurocomputing (2014)
Keyphrases
- random forest
- angiography images
- computed tomography
- contrast enhanced
- active learning
- vessel enhancement
- carotid artery
- medical images
- medical imaging
- ct images
- vessel segmentation
- vessel tree
- decision trees
- low contrast
- active shape model
- feature set
- ct data
- ct scans
- image reconstruction
- multiscale
- contrast agent
- region growing
- three dimensional
- ensemble methods
- computer tomography
- multi label
- ultrasound images
- fully automatic
- segmentation method
- accurate segmentation
- magnetic resonance
- deformable models
- retinal images
- image analysis
- image processing
- mr images
- imaging modalities
- computer aided diagnosis
- anatomical structures
- magnetic resonance imaging
- automatic segmentation
- x ray