Reducing the effect of false positives in classification of detected clustered microcalcifications.
Maria V. Sainz de CeaYongyi YangRobert M. NishikawaPublished in: ISBI (2018)
Keyphrases
- false positives
- false negative
- detection rate
- computer aided diagnosis
- clustered microcalcifications
- true positive
- number of false positives
- false positive rate
- false detections
- machine learning
- feature extraction
- digital mammograms
- low false positive rate
- classification accuracy
- feature vectors
- pattern recognition
- false alarms
- support vector
- digitized mammograms
- feature selection
- decision trees
- textural features
- texture analysis
- feature space
- training data