Classification of breast abnormality using decision tree based on GLCM features in mammograms.
J. KamalakannanM. Rajasekhara BabuPublished in: Int. J. Comput. Aided Eng. Technol. (2018)
Keyphrases
- mammogram images
- textural features
- digital mammograms
- digitized mammograms
- benign and malignant
- classification accuracy
- feature vectors
- grey level co occurrence matrix
- breast cancer
- feature set
- feature extraction
- breast tissue
- classification process
- mammographic images
- classification method
- extracted features
- feature space
- classification models
- benchmark datasets
- high dimensionality
- extracting features
- svm classifier
- breast cancer diagnosis
- feature analysis
- texture analysis
- feature selection
- computer aided diagnosis
- discriminative features
- decision trees
- feature representation
- class labels
- feature selection algorithms
- pectoral muscle
- grey level
- feature subset
- texture features
- text classification
- supervised learning
- image segmentation
- multiscale
- pattern recognition
- breast mri
- training set
- support vector machine
- naive bayes
- edge enhancement
- logistic regression
- gabor filters
- eeg signals