calcThreshold: Image thresholding

Description

Threshold a contrast parameter at one or several values.

Usage

## S3 method for class 'MRIaggr':
calcThresholdMRIaggr(object, param, hemisphere = "both", rm.CSF = FALSE,
     threshold = 1:10, decreasing = FALSE,
	 GRalgo = FALSE, W = "ifany", seed = NULL, numeric2logical = FALSE, W.range,
	 W.spatial_res = rep(1,3), name_newparam = paste(param,"Th", sep = "_"),
	 verbose = optionsMRIaggr("verbose"), update.object = FALSE, overwrite = FALSE)
	 
calcThreshold(contrast, param, hemisphere = NULL, rm.CSF = FALSE, threshold = 1:10,
     decreasing = FALSE, GRalgo = FALSE, W = NULL, seed = NULL,
     numeric2logical = FALSE, verbose = optionsMRIaggr("verbose"))

Arguments

object

an object of class MRIaggr. REQUIRED.

contrast

the dataset containing the contrast parameter to be thresholded. matrix. REQUIRED.

param

the contrast parameters to be thresholded. character vector. REQUIRED.

hemisphere

the hemisphere to consider. character or NULL.

rm.CSF

should the cerebral spinal fluid observations be excluded ? logical or character.

threshold

the thresholds to be used for the discretization of the contrast parameter. numeric vector.

decreasing

should the increasing thresholding (FALSE) or decreasing thresholding (TRUE) be used. logical.

GRalgo

should a Growing Region algorithm be used to clean the thresholded parameter ? logical.

the neighbourhood matrix. dgCMatrix or "ifany" leading to use the neighbourhood matrix stored in the object if any and else computate this matrix.

seed

the index of the seeds for the growing region algorithm . positive integer vector.

numeric2logical

should seed be converted to logical ? logical.

W.range

only distances smaller than W.range are stored in W. postive numeric.

W.spatial_res

a dilatation factor for the coordinates. positive numeric vector of size 3.

name_newparam

the name of the new parameters. character.

verbose

should the execution of the function be traced ? logical.

update.object

should the resulting thresholded parameters be stored in object ? logical.

overwrite

contrast parameters with the same names are already stored in object@data, can it be overwritten ? logical.

Details

These functions require to have installed the Matrix and the spam package to work when argument GRalgo is set to TRUE. ARGUMENTS: [data.frame method] the hemisphere argument must be one of the levels present in the column named "hemisphere" in data. NULL leading to use all observations. [MRIaggr method] Information about the hemisphere arguments can be found in the details section of selectContrast. FUNCTION: [data.frame method] By default the indicator of CSF will be extract from the column named CSF. If it is contained in another column the user must specify rm.CSF with the name of this column. [MRIaggr method] Setting rm.CSF to TRUE require to have the corresponding parameter (by default CSF) stored in the object. It can be done using calcTissueType.

References

Chantal Revol and Michel Jourlin. A new minimum varance region growing algorithm for image segmentation. Pattern Recognition Letters, 18(3):249-258,1997.

Examples

Run this code

## load a MRIaggr object
data(MRIaggr.Pat1_red, package = "MRIaggr")

#### 1- MRIaggr method 
## raw parameter
multiplot(MRIaggr.Pat1_red, param = "TTP_t0", legend = FALSE, main = "TTP_t0 - slice ",
             palette=rainbow(10), breaks = seq(0,10) - 10^{-10})

## thresholded parameter
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)

multiplot(MRIaggr.Pat1_red, param = "TTP.th_t0", main = "TTP.th_t0 - slice",
             legend = FALSE,palette = rainbow(10), breaks = (0:10) - 10^{-10})

## 1st correction
calcThresholdMRIaggr(MRIaggr.Pat1_red, param = c("TTP_t0","MTT_t0"),threshold = 1:10,
                 rm.CSF = TRUE, hemisphere = "lesion", 
				 name_newparam = c("TTP.red_t0","MTT.red_t0"),
				 update.object = TRUE, overwrite = TRUE)

multiplot(MRIaggr.Pat1_red, param = "TTP.red_t0", main = "TTP.red_t0 - slice",
             legend = FALSE, palette = rainbow(10), breaks = (0:10) - 10^{-10})

## 2nd correction
calcThresholdMRIaggr(MRIaggr.Pat1_red, param = c("TTP_t0","MTT_t0"), threshold = 1:10,
         rm.CSF = TRUE, hemisphere = "lesion", name_newparam = c("TTP.GR_t0","MTT.GR_t0"),
         GRalgo = TRUE, seed = c("MASK_T2_FLAIR_t2","MASK_DWI_t0"), W.range  = sqrt(2),
         update.object = TRUE, overwrite = TRUE)

multiplot(MRIaggr.Pat1_red, param = "TTP.GR_t0", main = "TTP.GR_t0 - slice",
             legend = FALSE, palette = rainbow(10), breaks = (0:10) - 10^{-10})


#### 2- data.frame function ####

## raw parameter
multiplot(MRIaggr.Pat1_red, param = "TTP_t0", legend = FALSE, main = "TTP_t0 - slice ",
         palette=rainbow(10), breaks = seq(0,10) - 10^{-10})

## thresholded parameter 
data <- selectContrast(MRIaggr.Pat1_red, 
                       param = c("TTP_t0","MTT_t0","hemisphere","CSF","WM","GM"))
hypo_Th1_10 <- calcThreshold(data,param = c("TTP_t0","MTT_t0"), threshold = 1:10)

multiplot(selectCoords(MRIaggr.Pat1_red), main = "TTP_t0_th - slice ",
             hypo_Th1_10[,1], legend = FALSE, palette = rainbow(10), breaks = (0:10) - 10^{-10})

## 1st correction
data$CSF <- as.numeric(apply(data[,c("CSF","WM","GM")], 1, which.max) == 1)

hypoC_Th1_10 <- calcThreshold(data,param = c("TTP_t0","MTT_t0"), threshold = 1:10,
                              hemisphere = "left", rm.CSF = TRUE)

multiplot(selectCoords(MRIaggr.Pat1_red), main = "TTP_t0_thC - slice",
          hypoC_Th1_10[,1], legend = FALSE, palette = rainbow(10), breaks = (0:10) - 10^{-10})

## 2nd correction
maskN <- c("MASK_T2_FLAIR_t2","MASK_DWI_t0")
data[, maskN] <- selectContrast(MRIaggr.Pat1_red, param = maskN)
W <- calcW(MRIaggr.Pat1_red, range  = sqrt(2 * 1.875^2 + 0.001), row.norm = TRUE, upper = NULL,
           spatial_res = c(1.875,1.875,6))$W
max(spam::rowSums(W > 0))

hypoCC_Th1_10 <- calcThreshold(data, param = c("TTP_t0","MTT_t0"), threshold = 1:10,
                    hemisphere = "left", rm.CSF = TRUE,
                    GRalgo = TRUE, seed = c("MASK_T2_FLAIR_t2","MASK_DWI_t0"), W = W)

multiplot(selectCoords(MRIaggr.Pat1_red), main = "TTP_t0_thCC  - slice",
          hypoCC_Th1_10[,1], legend = FALSE, palette = rainbow(10), breaks = (0:10) - 10^{-10})