Description Usage Arguments See Also Examples
Display the quality criteria for various values of sigma using the result of the calcSigmaGR
function.
1 2 3 4 5 6 | 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", ...)
|
calcSigmaGR |
an object generated by the |
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 : |
calcSigmaGR
to compute the quality criteria.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## 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")
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