quality.check {GoodFibes}

Quality testing of possible muscle fibers detected by good.fibes

Description

Calculates quality as the ratio of grayscale standard deviation and fiber length for each muscle fiber detected using good.fibes. Long, homogenous fibers are considered to be of higher quality. Fibers are smoothed before the calculation of fiber quality.

Fibers with usually low quality (high grayscale variation compared to fiber length) are identified for exclusion.

Usage

quality.check(fib.list, images, res, min.length = NULL, length.out = 200, df = 2)

Arguments

fib.list

A list of muscle fibers with $fiber.points, generated by good.fibes

images

A character vector of image stack file names. Generated with list.files

res

The isometric resolution of the voxels (i.e., the distance between images). Given as a linear measure (um, mm, etc.)

min.length

Optionally exclude fibers below a certain fiber length (e.g., based on anatomical measurements). If resolution is given, then in those units, otherwise in number of voxels.

length.out

Number of line segments used in the calculation of fiber length

df

Degrees of freedom passed to splines::ns in the smoothing of muscle fibers before calculation. df = 1 produces straight fibers, while values > 1 produce increasingly curved fibers

Value

quality

grayscale sd/fiber length, low values are considered of higher quality

grey.values

A list providing the grayscale values for each smoothed fibers

problem.fibers

The location of fibers in the original list object that have atypically poor quality and should be excluded from further analyses

Note

Also produces a plot showing the distribution of quality values, and numbered bars for outliers.

Author(s)

J. Arbour

References

Arbour, J. In Prep. GoodFibes: an R package for the detection of muscle fibers from diceCT scans.

Puffel, F. Pouget, A., Liu, X., Zuber, M., van de Kamp, T., Roces, F., and Labonte, D., 2021. Journal of the Royal Society Interface 18: 20210424

See Also

fuse.fibers,check.overlap,

Examples

olddir<-getwd()

#### this downloads the ant dataset image stack
#### if you have it already downloaded you can navigate to that folder
setwd(tempdir())
download.file(url=
"https://github.com/jessica-arbour/Ant-Muscle-Image-Stack/raw/main/Ant_data.zip",
destfile="antdata.zip")

unzip("antdata.zip")
setwd(paste0(getwd(),"/Ant data"))
####

data(ant.raw)
images<-list.files(pattern=".png")

qc<-quality.check(ant.raw[21:50],images, res=0.000673107, df=1)


setwd(olddir)