createHypothalamusUnetModel3D: 3-D u-net architecture for hypothalamus segmentation

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

3-D u-net architecture for hypothalamus segmentation

Description

Implementation of the U-net architecture for hypothalamus segmentation described in

Usage

createHypothalamusUnetModel3D(inputImageSize)

Arguments

inputImageSize

Used for specifying the input tensor shape. The shape (or dimension) of that tensor is the image dimensions only (number of channels is 1).

Details

https://pubmed.ncbi.nlm.nih.gov/32853816/

and ported from the original implementation:

   https://github.com/BBillot/hypothalamus_seg

The network has is characterized by the following parameters:

• 3 resolution levels: 24 —> 48 —> 96 filters

• convolution: kernel size: c(3, 3, 3), activation: 'elu'

• pool size: c(2, 2, 2)

Value

a u-net keras model

Author(s)

Tustison NJ

Examples

# Simple examples, must run successfully and quickly. These will be tested.

library( ANTsRNet )

model <- createHypothalamusUnetModel3d( c( 160, 160, 160 ) )

print( model )

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