MRIaggr (version 1.1.5)

plotSigmaGR: Display quality criteria for the GR algorithm

Description

Display the quality criteria for various values of sigma using the result of the calcSigmaGR function.

Usage

plotSigmaGR(calcSigmaGR, mar = c(3, 3, 2, 2), mgp = c(2, 0.75, 0), main = "", col = c("black", grDevices::rainbow(5)), criterion = c("n.obs", "transition", "sdfront", "entropy", "Kalinsky", "Laboure"), name_criteria = c("region size", "boundary transition", "boundary heterogeneity",  "region entropy", "region Kalinsky", "region Laboure"),  filename = "calcSigmaGR", ...)

Arguments

calcSigmaGR

an object generated by the calcSigmaGR function. REQUIRED.

mar

the number of margin lines to be specified on the four sides of the plot. positive numeric vector of size 4.

mgp

the margin line for the axis title, axis labels and axis line. positive numeric vector of size 3.

main

an overall title for the plot. character.

col

the color to use to plot each criterion. character vector.

criterion

the criterion to be displayed. character vector.

name_criteria

the name to be used in the legend. character vector.

filename

the name of the file used to export the plot. character.

...

additional arguments for the graphical device : window, width, height, path, unit, res (see optionsMRIaggr).

See Also

calcSigmaGR to compute the quality criteria.

Examples

## load an \code{MRIaggr} object
data(MRIaggr.Pat1_red, package = "MRIaggr")

calcThresholdMRIaggr(MRIaggr.Pat1_red,param = c("TTP_t0","MTT_t0"), threshold = 1:10,
                     name_newparam = c("TTP.th_t0","MTT.th_t0"),
                     update.object = TRUE, overwrite = TRUE)

## display raw parameter
multiplot(MRIaggr.Pat1_red, param = "TTP.th_t0", num = 3, numeric2logical = TRUE,
          index1 = list(coords = "MASK_DWI_t0", outline = TRUE))

## extract raw parameter, coordinates and compute the neighbourhood matrix
carto <- selectContrast(MRIaggr.Pat1_red, num = 3, hemisphere = "lesion",
                        param = c("TTP.th_t0","TTP_t0","MASK_DWI_t0"))
coords <- selectCoords(MRIaggr.Pat1_red, num = 3, hemisphere = "lesion")
W <- calcW(coords, range = sqrt(2))$W

## the seed is taken to be the point with the largest TTP in the lesion mask
indexN <- which(carto$MASK_DWI_t0 == 1)
seed <- indexN[which.max(carto[indexN,"TTP_t0"])]

## find optimal sigma
resGR_sigma <- calcSigmaGR(contrast = carto$TTP.th_t0, W = W, seed = seed,
                           sigma = seq(1,4,0.1), iter_max = 50,
                           keep.upper = TRUE)

## display quality criteria according to sigma
plotSigmaGR(resGR_sigma)

plotSigmaGR(resGR_sigma, criterion = "entropy")