Implementation of the "SCFN" architecture for Brain/Gender prediction

Creates a keras model implementation of the Simple Fully Convolutional Network model from the FMRIB group:

createSimpleFullyConvolutionalNeuralNetworkModel3D(
  inputImageSize,
  numberOfFiltersPerLayer = c(32, 64, 128, 256, 256, 64),
  numberOfBins = 40,
  dropoutRate = 0.5,
  doExperimentalVariant = FALSE
)

Arguments

inputImageSize	Used for specifying the input tensor shape. The shape (or dimension) of that tensor is the image dimensions followed by the number of channels (e.g., red, green, and blue).
numberOfFiltersPerLayer	number of filters for the convolutional layers
numberOfBins	number of bins for final softmax output.
dropoutRate	dropout rate before final convolution layer.

Value

a SCFN keras model

Details

    \url{https://github.com/ha-ha-ha-han/UKBiobank_deep_pretrain}

Author

Tustison NJ

Examples

library( ANTsRNet )

model <- createSimpleFullyConvolutionalNeuralNetworkModel3D( list( NULL, NULL, NULL, 1 ) )
#> Error in py_discover_config(required_module, use_environment): Python specified in RETICULATE_PYTHON (/Users/ntustison/anaconda3/envs/antsx/bin/python3) does not exist