Reducing annotation cost and uncertainty in computer-aided diagnosis through selective iterative classification.
Amelia RielyKyle SablanThomas XiaotaoJacob D. FurstDaniela RaicuPublished in: Medical Imaging: Computer-Aided Diagnosis (2015)
Keyphrases
- computer aided diagnosis
- lung nodules
- computer aided
- medical images
- breast cancer
- clustered microcalcifications
- high resolution computed tomography
- machine learning
- lesion detection
- ct scans
- image analysis
- pattern recognition
- medical imaging
- classification accuracy
- feature selection
- mammogram images
- digital mammography
- cad systems
- cost sensitive
- decision trees
- feature extraction
- ct images
- feature vectors
- computer vision
- text classification
- three dimensional
- image processing
- active learning
- high resolution
- training set
- feature space