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Plot ROI, SCC detections, and SPM detections for validation

Source: R/plotValidationPanel.R
plotValidationPanel.Rd

This function visualizes the ground-truth ROI, SCC-detected points, and SPM-detected points as a three-panel comparison over a shared neuroimaging background.

Usage

plotValidationPanel(
  template,
  backgroundMatrix,
  roiPoints,
  sccPoints,
  spmPoints,
  title = "COMPARISON PANEL",
  label1 = "True ROI",
  label2 = "SCC Detected",
  label3 = "SPM Detected"
)

Arguments

template

character, path to a NIfTI file used to obtain the grid dimensions of the imaging domain.

backgroundMatrix

A numeric matrix used to generate the grayscale background image.

roiPoints

A data.frame with columns x and y containing the ground-truth ROI points.

sccPoints

A list containing positivePoints and negativePoints, each as a data.frame with columns x and y.

spmPoints

A data.frame with columns x and y containing the SPM-detected points.

title

character, title shown above the panel.

label1

character, title of the ground-truth ROI panel.

label2

character, title of the SCC-detected panel.

label3

character, title of the SPM-detected panel.

Value

A patchwork/ggplot object containing three aligned panels:

  • ground-truth ROI,

  • SCC-detected points,

  • SPM-detected points.

Details

The three panels share the same grayscale background to facilitate visual comparison between the true ROI and the points detected by SCC and SPM.

In the examples, SCC detections are restricted to positive points only to keep the visualization simple. With real analysis outputs, sccPoints would typically be supplied directly as getPoints(<SCC object>).

See also

SCCcomp for the example SCC object used in the examples.
getPoints for extraction of SCC-detected significant points.
getSPMbinary for extraction of SPM-detected significant points.
processROIs for extraction of ground-truth ROI points.

Examples

# \donttest{
paramZ <- 35

controlPattern <- "^syntheticControl.*\\.nii\\.gz$"
databaseCN <- databaseCreator(pattern = controlPattern, control = TRUE, quiet = TRUE)
matrixCN <- matrixCreator(database = databaseCN, paramZ = paramZ, quiet = TRUE)
matrixCN <- meanNormalization(matrixCN)
#> 
#>  Mean before normalization: 4.345851
#> 
#>  Normalization completed.

roiFile <- system.file("extdata", "ROIsample_Region2_18.nii.gz", package = "neuroSCC")
truePoints <- processROIs(roiFile, region = "Region2", number = "18", save = FALSE)
#> Loading NIfTI file...
roiPoints <- subset(truePoints, z == paramZ & pet == 1, select = c("x", "y"))

spmFile <- system.file("extdata", "binary.nii.gz", package = "neuroSCC")
spmPoints <- getSPMbinary(spmFile, paramZ = paramZ)

data("SCCcomp", package = "neuroSCC")

plotValidationPanel(
  template = roiFile,
  backgroundMatrix = matrixCN,
  roiPoints = roiPoints,
  sccPoints = list(
    positivePoints = getPoints(SCCcomp)$positivePoints,
    negativePoints = data.frame(x = numeric(0), y = numeric(0))
  ),
  spmPoints = spmPoints,
  title = "Performance Validation Panel",
  label1 = "Ground Truth (ROI)",
  label2 = "SCC Detected",
  label3 = "SPM Detected"
)

# }