createPartialConvolutionUnetModel2D: 2-D implementation of the U-net architecture for inpainting...

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

2-D implementation of the U-net architecture for inpainting using partial convolution.

Description

    \url{https://arxiv.org/abs/1804.07723}

Usage

createPartialConvolutionUnetModel2D(
  inputImageSize,
  numberOfPriors = 0,
  numberOfFilters = c(64, 128, 256, 512, 512, 512, 512, 512),
  kernelSize = c(7, 5, 5, 3, 3, 3, 3, 3),
  usePartialConv = TRUE
)

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). The batch size (i.e., number of training images) is not specified a priori.
numberOfPriors	Specify tissue priors for use during the decoding branch. Default = 0.
numberOfFilters	vector explicitly setting the number of filters at each layer. Defaults to number used in the paper.
kernelSize	single scalar or tuple of same length as the number of filters. Specifies the kernel size schedule for the encoding path. Defaults to the kernel sizes used in the paper.
usePartialConv	boolean. Testing. Switch between vanilla convolution layers and partial convolution layers.

Value

a u-net keras model

Author(s)

Tustison NJ

ANTsX/ANTsRNet documentation built on Nov. 25, 2024, 10:27 p.m.