Training sample selection based on self-training for liver cirrhosis classification using ultrasound images.
Yusuke FujitaYoshihiro MitaniYoshihiko HamamotoMakoto SegawaShuji TeraiIsao SakaidaPublished in: QCAV (2017)
Keyphrases
- training samples
- ultrasound images
- training set
- decision boundary
- ultrasound probe
- training data
- feature space
- medical ultrasound
- speckle noise
- supervised learning
- classification accuracy
- learning algorithm
- class labels
- support vector machine svm
- classification method
- training examples
- edge detection
- support vector machine
- decision trees
- machine learning
- active learning
- ct images
- high dimensional
- speckle reduction
- ultrasound imaging
- feature selection
- data sets
- image sequences
- test sample