N3 Bias field correction

Perform N3 bias field correction on the given image

n3BiasFieldCorrection2(
  img,
  mask,
  rescaleIntensities = FALSE,
  shrinkFactor = 4,
  convergence = list(iters = 50, tol = 1e-07),
  splineParam = 200,
  numberOfFittingLevels = 4,
  weightMask = NULL,
  returnBiasField = FALSE,
  verbose = FALSE
)

Arguments

img

input antsImage

mask

input mask, if one is not passed one will be made

rescaleIntensities

At each iteration, a new intensity mapping is calculated and applied but there is nothing which constrains the new intensity range to be within certain values. The result is that the range can "drift" from the original at each iteration. This option rescales to the [min,max] range of the original image intensities within the user-specified mask. A mask is required to perform rescaling. Default is FALSE in ANTsR/ANTsPy but TRUE in ANTs.

shrinkFactor

Shrink factor for multi-resolution correction, typically integer less than 4

convergence

List of: iters, maximum number of iterations and tol, the convergence tolerance. Default tolerance is 1e-7 in ANTsR/ANTsPy but 0.0 in ANTs.

splineParam

Parameter controlling number of control points in spline. Either single value, indicating how many control points, or vector with one entry per dimension of image, indicating the spacing in each direction. Default is a mesh size of 1 per dimension.

numberOfFittingLevels

Parameter controlling number of fitting levels.

weightMask

antsImage of weight mask

returnBiasField

bool, return the field instead of the corrected image.

verbose

enables verbose output.

Value

bias corrected image or bias field

Author

Avants BB, Tustison NJ

Examples

dims <- c(50, 50)
img <- makeImage(imagesize = dims, rnorm(prod(dims)))
n3img <- n3BiasFieldCorrection2(img)
n3img <- n3BiasFieldCorrection2(img, mask = img > 0)
testthat::expect_error(n3BiasFieldCorrection2(img, weightMask = "somepath"))
testthat::expect_error(n3BiasFieldCorrection2(img, splineParam = rep(200, 3)))
# n3img<-n3BiasFieldCorrection2(img, splineParam = c(200, 20)) # long running

rm(img)
gc()
#>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)
#> Ncells 4010922 214.3    5925935 316.5         NA  5925935 316.5
#> Vcells 6719379  51.3   15907889 121.4     102400 15907845 121.4
rm(n3img)
gc()
#>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)
#> Ncells 4010618 214.2    5925935 316.5         NA  5925935 316.5
#> Vcells 6718904  51.3   15907889 121.4     102400 15907845 121.4
fname <- getANTsRData("r16")
in_img <- antsImageRead(fname)
n3 <- n3BiasFieldCorrection2(in_img)
rm(n3)
gc()
#>           used  (Mb) gc trigger  (Mb) limit (Mb) max used  (Mb)
#> Ncells 4010678 214.2    5925935 316.5         NA  5925935 316.5
#> Vcells 6719000  51.3   15907889 121.4     102400 15907845 121.4
mask <- in_img > 0
mask2 <- antsImageClone(mask, out_pixeltype = "float")
# fails
mask
#> antsImage
#>   Pixel Type          : unsigned char 
#>   Components Per Pixel: 1 
#>   Dimensions          : 256x256 
#>   Voxel Spacing       : 1x1 
#>   Origin              : 0 0 
#>   Direction           : 1 0 0 1 
#> 
sum(mask)
#> [1] 19278
if (FALSE) { # \dontrun{
n3 <- n3BiasFieldCorrection2(in_img, mask = mask, verbose = TRUE)
# fails
n3 <- n3BiasFieldCorrection2(in_img, mask = mask2)
} # }