Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans.
Pierre-Henri ConzeVincent NobletFrançois RousseauFabrice HeitzVito de BlasiRiccardo MemeoPatrick PessauxPublished in: Int. J. Comput. Assist. Radiol. Surg. (2017)
Keyphrases
- ct scans
- random forests
- ct images
- tumor segmentation
- random forest
- x ray
- computed tomography
- decision trees
- ct data
- machine learning algorithms
- logistic regression
- computer aided diagnosis
- region of interest
- ensemble methods
- mri data
- brain tumors
- computer aided
- mr images
- registration accuracy
- active contour model
- image reconstruction
- feature set
- image analysis
- pattern recognition