Texture analysis and multiple-instance learning for the classification of malignant lymphomas.
Marco LippiStefania GianottiAngelo FamaMassimiliano CasaliElisa BarboliniAngela FerrariFederica FioroniMauro IoriStefano LuminariMassimo MengaFrancesco MerliValeria TrojaniAnnibale VersariMagda ZanelliMarco BertoliniPublished in: Comput. Methods Programs Biomed. (2020)
Keyphrases
- texture analysis
- multiple instance learning
- texture discrimination
- image categorization
- supervised learning
- multiple instance
- feature extraction
- gabor filtering
- textural features
- brodatz textures
- gray level
- texture classification
- multi class
- multiresolution
- image analysis
- pattern recognition
- gabor filters
- class labels
- co occurrence
- classification accuracy
- feature vectors
- decision trees
- texture features
- texture descriptors
- training set
- local binary pattern
- semi supervised
- support vector
- breast tissue
- text classification
- neural network
- image classification
- machine learning
- logistic regression
- visual features
- unsupervised learning
- regression problems
- object recognition
- multiscale
- image segmentation
- image processing
- data mining