mriSuperResolution: Super-resolution for MRI

In ANTsX/ANTsRNet: Neural Networks for Medical Image Processing

Super-resolution for MRI

Description

Perform super-resolution of MRI data using deep back projection network. Work described in

https://www.medrxiv.org/content/10.1101/2023.02.02.23285376v1

with the GitHub repo located at https://github.com/stnava/siq

Note that some preprocessing possibilities for the input includes:

• Truncate intensity (see ants.iMath(..., 'TruncateIntensity', ...)

Usage

mriSuperResolution(
  image,
  expansionFactor = c(1, 1, 2),
  feature = "vgg",
  targetRange = c(1, 0),
  polyOrder = "hist",
  verbose = FALSE
)

Arguments

image	magnetic resonance image
expansionFactor	Specifies the increase in resolution per dimension. Possibilities include: c(1,1,2), c(1,1,3), c(1,1,4), c(1,1,6), c(2,2,2), and c(2,2,4).
feature	"grader" or "vgg"
targetRange	Range for applySuperResolutionModel.
polyOrder	int or the string 'hist'. Parameter for regression matching or specification of histogram matching.
verbose	print progress.

Value

super-resolution image.

Author(s)

Avants BB

Examples

## Not run: 
library( ANTsRNet )

image <- antsImageRead( "t1.nii.gz" )
imageSr <- mriSuperResolution( image )

## End(Not run)

ANTsX/ANTsRNet documentation built on Feb. 19, 2025, 11:22 p.m.