Exploratory learning with convolutional autoencoder for discrimination of architectural distortion in digital mammography.
Helder Cesar Rodigues de OliveiraCarlos F. E. MeloJuliana H. CataniNestor de BarrosMarcelo Andrade da Costa VieiraPublished in: Medical Imaging: Computer-Aided Diagnosis (2019)
Keyphrases
- exploratory learning
- digital mammography
- restricted boltzmann machine
- computer aided diagnosis
- breast cancer
- computer simulation
- scientific inquiry
- guided exploration
- digital mammograms
- learning environment
- deep learning
- computer aided
- medical images
- feature selection
- software architecture
- learning algorithm
- medical imaging
- information sharing
- pattern recognition
- decision trees