createConvolutionalAutoencoderModel3D: Function for creating a 3-D symmetric convolutional...

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

Function for creating a 3-D symmetric convolutional autoencoder model.

Description

Builds a convolutional autoencoder based on the specified array definining the number of units in the encoding branch. Ported to Keras R from the Keras python implementation here:

Usage

createConvolutionalAutoencoderModel3D(
  inputImageSize,
  numberOfFiltersPerLayer = c(32, 64, 128, 10),
  convolutionKernelSize = c(5, 5, 5),
  deconvolutionKernelSize = c(5, 5, 5)
)

Arguments

inputImageSize	vector definining spatial dimensions + channels
numberOfFiltersPerLayer	vector defining the number of convolutional filters in the encoding branch per layer
convolutionKernelSize	kernel size fo the convolutional filters
deconvolutionKernelSize	kernel size fo the convolutional transpose filters

Details

https://github.com/XifengGuo/DCEC

Value

two models: the convolutional encoder and convolutional auto-encoder

Author(s)

Tustison NJ

Examples

library( ANTsRNet )
library( keras )

ae <- createConvolutionalAutoencoderModel2D( c( 32, 32, 1 ) )

ANTsX/ANTsRNet documentation built on April 23, 2024, 1:24 p.m.