mincSummary: Minc Voxel Summary Functions

In Mouse-Imaging-Centre/RMINC: Statistical Tools for Medical Imaging NetCDF (MINC) Files

Minc Voxel Summary Functions

Description

Compute the mean, standard deviation, sum, or variance at every voxel across a a set of MINC volumes. An optional grouping variable will split the computation by group rather than performing it across all volumes as is the default.

Usage

mincSummary(
  filenames,
  grouping = NULL,
  mask = NULL,
  method = "mean",
  maskval = NULL
)

mincMean(filenames, grouping = NULL, mask = NULL, maskval = NULL)

mincVar(filenames, grouping = NULL, mask = NULL, maskval = NULL)

mincSum(filenames, grouping = NULL, mask = NULL, maskval = NULL)

mincSd(filenames, grouping = NULL, mask = NULL, maskval = NULL)

mincCorrelation(filenames, grouping, mask = NULL, maskval = NULL)

Arguments

filenames	Filenames of the MINC volumes across which to create the descriptive statistic.
grouping	Optional grouping - contains same number of elements as filenames; the results will then have the descriptive statistic computed separately for each group, or in the case of method = "correlation" this is the variable to correlate against.
mask	A mask specifying which voxels are to be included in the summary.
method	the type of summarys statistic to calculate for each voxel
maskval	the value in the mask used to select unmasked voxels, defaults to any positive intensity from 1-99999999 internally expanded to .5 - 99999999.5. If a number is specified voxels with intensities within 0.5 of the chosen value are considered selected.

Value

The output will be a single vector containing as many elements as there are voxels in the input files. If a grouping factor was specified then the output will be a matrix consisiting of as many rows as there were voxels in the files, and as many columns as there were groups.

Functions

• mincMean: mean

• mincVar: Variance

• mincSum: Sum

• mincSd: Standard Deviation

• mincCorrelation: Correlation

Examples

## Not run: 
getRMINCTestData() 
gf <- read.csv("/tmp/rminctestdata/minc_summary_test_data.csv") 
mm <- mincMean(gf$jacobians_0.2) 
ms <- mincSd(gf$jacobians_0.2)
mv <- mincVar(gf$jacobians_0.2,gf$Strain) 
ms2 <- mincSum(gf$jacobians_0.2,gf$Strain)

## End(Not run)

Mouse-Imaging-Centre/RMINC documentation built on Nov. 12, 2022, 1:50 p.m.