Automatic Lung Segmentation in CT Images Using Mask R-CNN for Mapping the Feature Extraction in Supervised Methods of Machine Learning.
Luís Fabrício de F. SouzaGabriel Bandeira HolandaShara S. A. AlvesFrancisco Hércules dos S. SilvaPedro Pedrosa Rebouças FilhoPublished in: ISDA (2019)
Keyphrases
- ct images
- medical images
- machine learning
- supervised methods
- feature extraction
- pet ct
- medical imaging
- semantic segmentation
- lung parenchyma
- computed tomography
- lung nodules
- ct scans
- fracture detection
- computer tomography
- fully automatic
- ground glass opacity
- pet images
- labor intensive
- pattern recognition
- feature selection
- image segmentation
- region of interest
- image processing
- weakly supervised
- pulmonary nodules
- computer vision
- decision trees
- image analysis
- computer aided diagnosis
- segmentation algorithm
- supervised learning
- segmentation method
- ct data
- deformable models
- feature space
- information extraction
- face recognition
- level set
- lymph nodes
- labeled data
- energy function
- mr images
- graph cuts
- image registration
- bounding box