Feature Selection Based on Gaussian Mixture Model Clustering for the Classification of Pulmonary Nodules Based on Computed Tomography.
Huihong DuanXu WangXingyi HeYonggang HeLitao SongShengdong NiePublished in: J. Medical Imaging Health Informatics (2020)
Keyphrases
- computed tomography
- gaussian mixture model
- pulmonary nodules
- ct images
- feature selection
- thoracic ct images
- ct scans
- lung nodules
- feature space
- feature vectors
- medical images
- unsupervised learning
- medical imaging
- image reconstruction
- support vector
- mixture model
- density estimation
- feature extraction
- ct data
- three dimensional
- text classification
- expectation maximization
- machine learning
- computer aided diagnosis
- em algorithm
- computer aided
- maximum likelihood
- decision trees
- low dose
- k means
- model selection
- pattern recognition
- clustering algorithm
- region of interest
- dimensionality reduction
- lung cancer
- medical domain
- supervised learning
- computer tomography
- computer vision
- information retrieval