Perform simple segmentation of multiplexed cellular images
Usage
simpleSeg(
image,
nucleus,
cellBody = "dilate",
sizeSelection = 10,
smooth = 1,
transform = NULL,
watershed = "combine",
tolerance = NULL,
ext = 1,
discSize = 3,
tissue = NULL,
pca = FALSE,
cores = 1
)Arguments
- image
An image or list of images or CytoImageList to be read into the function.
- nucleus
The marker or list of markers corresponding to the nuclei.
- cellBody
Method of cytoplasm identification. Can be 'none', dilate', 'discModel' or the name of a dedicated cytoplasm marker
- sizeSelection
Minimum pixels for an object to be recognized as a cell and not noise.
- smooth
The amount of Gaussian smoothing to be applied to the image/s
- transform
A transformation or list of transformations and normalizations to be performed prior to nuclei or cytoplasm identification. Accepted vales: "sqrt", "asinh", "norm99", "maxThresh" and "tissueMask". Tissue mask may be used when the sample does not take up the entirety of the image (typically a circular sample inside the image. When tissue mask is specified the background noise present outside the sample area is removed).
- watershed
Method used to perform watersheding. Accepted values: "distance" or "combine".
- tolerance
The minimum height of the object in the units of image intensity between its highest point (seed) and the point where it contacts another object (checked for every contact pixel). If the height is smaller than the tolerance, the object will be combined with one of its neighbors, which is the highest. Tolerance should be chosen according to the range of x. Default value is 1, which is a reasonable value if x comes from distmap.
- ext
Radius of the neighborhood in pixels for the detection of neighboring objects. Higher value smooths out small objects.
- discSize
The size of dilation around nuclei to create cell disc or capture cytoplasm
- tissue
Channels to be used to create the tissue mask if specified in transforms.
- pca
Whether to run PCA on aggregated nucleus markers in order to detect the cellular nucclei.
- cores
The number or cores for parallel processing or a BPPARAM object
Examples
library(cytomapper)
data("pancreasImages")
masks <- simpleSeg(pancreasImages,
nucleus = "H3",
cellBody = "discModel",
sizeSelection = 8,
smooth = 1.2,
transform = "sqrt",
watershed = "combine",
tolerance = 1, ext = 1,
discSize = 3,
cores = 5
)