Accurate Segmentation of CT Male Pelvic Organs via Regression-Based Deformable Models and Multi-Task Random Forests.
Yaozong GaoYeqin ShaoJun LianAndrew Z. WangRonald C. ChenDinggang ShenPublished in: IEEE Trans. Medical Imaging (2016)
Keyphrases
- random forests
- deformable models
- multi task
- accurate segmentation
- medical images
- mr images
- computed tomography
- ct images
- soft tissue
- treatment planning
- ct data
- ct scans
- medical imaging
- magnetic resonance
- automatic segmentation
- random forest
- learning tasks
- magnetic resonance images
- machine learning algorithms
- decision trees
- imaging modalities
- logistic regression
- shape prior
- ensemble methods
- region of interest
- multi class
- feature selection
- active shape model
- active appearance models
- segmentation result
- level set method
- low contrast
- image segmentation
- computer vision
- multi label
- principal component analysis
- pairwise