Training Deep Neural Networks for Small and Highly Heterogeneous MRI Datasets for Cancer Grading.
Marek WodzinskiTommaso BanzatoManfredo AtzoriVincent AndrearczykYashin Dicente CidHenning MüllerPublished in: EMBC (2020)
Keyphrases
- highly heterogeneous
- neural network
- training process
- labeled data for training
- training algorithm
- feedforward neural networks
- training dataset
- feed forward neural networks
- training data
- multi layer perceptron
- back propagation
- neural network training
- training set
- magnetic resonance imaging
- gene expression profiles
- backpropagation algorithm
- mr images
- error back propagation
- training and testing data
- multi layer
- artificial neural networks
- pattern recognition
- neural nets
- breast cancer
- small number
- medical images
- data sets
- high resolution
- fuzzy logic
- deep architectures
- white matter
- logistic regression
- training examples
- prostate cancer
- supervised learning
- mri data
- gene selection
- feed forward
- support vector machine
- magnetic resonance images