bayesianCBF: Uses probabilistic segmentation to constrain pcasl-based cbf...

In neuroconductor-devel/ANTsR: ANTs in R: Quantification Tools for Biomedical Images

Description

Employs a robust regression approach to learn the relationship between a sample image and a list of images that are mapped to the same space as the sample image.

Usage

bayesianCBF(
  pcasl,
  segmentation,
  tissuelist,
  myPriorStrength = 30,
  useDataDrivenMask = 3,
  denoisingComponents = 1:8,
  robustnessvalue = 0.95,
  localweights = FALSE,
  priorBetas = NA
)

Arguments

pcasl	img antsImage for cbf
segmentation	image, should cover the brain.
tissuelist	a list containing antsImages eg list(prob1,...,probN)
myPriorStrength	- e.g 30
useDataDrivenMask	- morphology parameters e.g. 3
denoisingComponents	- data-driven denoising parameters
robustnessvalue	- value (e.g. 0.95) that throws away time points
localweights	Use estimate of voxel-wise reliability to inform prior weight?
priorBetas	prior betas for each tissue and predictor

Value

estimated cbf image

Author(s)

Brian Beaumont Avants and Benjamin M. Kandel

Examples

## Not run: 
set.seed(123)
# see fMRIANTs github repository for data and I/O suggestions

## End(Not run)

neuroconductor-devel/ANTsR documentation built on April 1, 2021, 1:02 p.m.