Random forests on hierarchical multi-scale supervoxels for liver tumor segmentation in dynamic contrast-enhanced CT scans.
Pierre-Henri ConzeVincent NobletFrançois RousseauFabrice HeitzRiccardo MemeoPatrick PessauxPublished in: ISBI (2016)
Keyphrases
- ct scans
- random forests
- tumor segmentation
- multiscale
- ct images
- computed tomography
- random forest
- x ray
- coarse to fine
- ct data
- brain tumors
- ensemble methods
- decision trees
- medical images
- mr images
- region of interest
- machine learning algorithms
- logistic regression
- computer aided diagnosis
- registration accuracy
- active contour model
- pulmonary nodules
- medical imaging
- mri data
- three dimensional
- machine learning