Exploiting Deep Cross-Slice Features From CT Images For Multi-Class Pneumonia Classification.
Jiawang CaoLulu JiangJunlin HouLongquan JiangRui-Wei ZhaoWeiya ShiFei ShanRui FengPublished in: ICIP (2021)
Keyphrases
- multi class
- ct images
- lung nodules
- multi class classification
- support vector machine
- multi class classifier
- binary classifiers
- multi class boosting
- binary and multi class
- cost sensitive
- feature vectors
- classification accuracy
- feature set
- multiple classes
- feature space
- feature selection
- computed tomography
- multi class svm
- feature extraction
- medical images
- svm classifier
- error correcting output codes
- multi class problems
- ct scans
- binary classification tasks
- binary classification
- support vector machine svm
- pairwise
- pulmonary nodules
- decision trees
- pattern classification
- region of interest
- class labels
- image features
- image classification
- object detection
- ground glass opacity
- pattern recognition
- multislice
- text classification
- support vector
- probabilistic boosting tree
- roc curve
- training samples
- naive bayes
- medical imaging
- eeg signals