Comparing two classes of end-to-end machine-learning models in lung nodule detection and classification: MTANNs vs. CNNs.
Nima TajbakhshKenji SuzukiPublished in: Pattern Recognit. (2017)
Keyphrases
- end to end
- machine learning models
- nodule detection
- lung nodules
- machine learning algorithms
- machine learning approaches
- spam filtering
- lung disease
- decision trees
- class labels
- ct images
- machine learning
- classification accuracy
- text classification
- text localization and recognition
- machine learning methods
- congestion control
- low dose
- classification models
- x ray images
- pulmonary nodules
- feature extraction
- vessel enhancement
- learning problems
- computer aided diagnosis
- pairwise
- feature space
- preprocessing
- support vector
- three dimensional
- learning algorithm