Description Usage Arguments Details Value See Also Examples
Converts raw CT units to material classes for each CT slice, directly replicating Earl Davey's manual classification approach. This method is deprecated as of coreCT version 1.3.0.
1 2 3 4 5 6 7 |
mat.list |
list of DICOM images for a sediment core (values in Hounsfield Units) |
upperLim |
upper bound cutoff for pixels (Hounsfield Units) |
lowerLim |
lower bound cutoff for pixels (Hounsfield Units) |
pixelA |
pixel area (mm2) |
thickness |
CT image thickness (mm) |
airHU |
mean value for air-filled calibration rod (Hounsfield Units) |
airSD |
standard deviation for air-filled calibration rod |
SiHU |
mean value for colloidal silica calibration rod |
SiSD |
standard deviation for colloidal Si calibration rod |
glassHU |
mean value for glass calibration rod |
glassSD |
standard deviation for glass calibration rod |
waterHU |
mean value for water filled calibration rod |
waterSD |
standard deviation for water filled calibration rod |
densities |
numeric vector of known cal rod densities. Format must be c(air, water, Si, glass) |
Calculates average Hounsfield units, cross-sectional areas (cm2), volumes (cm3), and masses (g) of material classes for each CT slice. This function assumes that core walls and all non-sediment material have been removed from the raw DICOM imagery. This function converts data from raw x-ray attenuation values to Hounsfield Units, and then uses user-defined calibration rod inputs to categorize sediment components: air, roots and rhizomes, peat, water, particulates, sand, and rock/shell.
value conv
returns a dataframe with one row per CT slice. Values returned are the average Hounsfield Unit value, the area (cm2), volume (cm3), and mass (grams) of 7 material classes: gas, peat, roots and rhizomes, particulates, sand, water, and rock/shell. If <code>rootData = TRUE</code>, data for specified root size classes are also returned. See <code>rootSize</code> for more detail on those values.
rootSize
operates similarly.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ct.slope <- unique(extractHeader(core_426$hdr, "RescaleSlope"))
ct.int <- unique(extractHeader(core_426$hdr, "RescaleIntercept"))
# convert raw units to Hounsfield units
HU_426 <- lapply(core_426$img, function(x) x*ct.slope + ct.int)
materials <- conv(HU_426, pixelA = 0.0596)
## Not run:
# plot using "ggplot" package after transforming with "reshape2" package
mass.long <- reshape2::melt(materials, id.vars = c("depth"),
measure.vars = grep(".g", names(materials)))
ggplot2::ggplot(data = mass.long, ggplot2::aes(y = -depth, x = value,
color = variable)) + ggplot2::geom_point() + ggplot2::theme_classic() +
ggplot2::xlab("mass per section (g)")
## End(Not run)
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