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.
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)
| 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. |
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.
mincMean: mean
mincVar: Variance
mincSum: Sum
mincSd: Standard Deviation
mincCorrelation: Correlation
# 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) # }