Automated classification of lung bronchovascular anatomy in CT using AdaBoost.
Robert A. OchsJonathan G. GoldinFereidoun AbtinHyun J. KimKathleen BrownPoonam BatraDonald RobackMichael F. McNitt-GrayMatthew S. BrownPublished in: Medical Image Anal. (2007)
Keyphrases
- automated classification
- ct images
- medical images
- computed tomography
- inter patient
- ct scans
- ct data
- medical imaging
- three dimensional
- lung parenchyma
- anatomical structures
- imaging modalities
- multi class
- computer tomography
- face detection
- object detection
- pulmonary embolism
- intraoperative
- learning algorithm
- pulmonary nodules
- support vector
- ground glass opacity
- target registration error
- lung nodules
- adaboost algorithm
- magnetic resonance
- image reconstruction
- treatment planning
- region of interest
- brain images
- lung disease
- lung cancer
- x ray
- computer aided diagnosis
- decision trees
- intra operatively
- low dose
- airway tree
- mr images
- boosting algorithms
- training data
- ensemble methods
- clinical applications
- chest radiographs
- magnetic resonance images
- dual energy
- ensemble learning
- thoracic ct images
- pet ct
- magnetic resonance imaging
- x ray images
- lymph nodes
- automatic segmentation
- patient specific
- weak classifiers
- completely automated
- feature selection
- computer vision