apply_mask: Apply a DAPI Mask over a Stacked Green Channel Image
In dami82/CellSignalingTools: Analysis of Images for Molecular Biology Applications

Description Usage Arguments Value Author(s) References Examples

Apply a DAPI mask over a specific antibody signal matrix (retrieved from an immunofluorescence TIFF image). Split the signal corresponding to a specific antibody (usually the green or the red channel) into nuclear and extra-nuclear areas based on DAPI Mask. Images in the Green/Red Channel and in the DAPI channel have to be perfectly stacked.

1	apply_mask(green_image, dapi_mask, bckgrnd = 0)

`green_image`	is a numeric matrix corresponding to signal intensity from an immunofluorescence TIFF image
`dapi_mask`	is a boolean matrix having the same dimensions as green_image. Typically, this is the result of a get_dapi_range() call.
`bckgrnd`	is a number in the range 0 to 0.9 and is used for background subtraction of the scaled (0 to 1) signals of the green_image

Returns a list of three numeric matrices having identical dimensions.

`nucl`	Signal intensities corresponding to nuclear areas of the green_image
`cyto`	Signal intensities corresponding to extra-nuclear areas of the green_image
`input`	Scaled and background-corrected input matrix (green_image)

Damiano Fantini

http://www.biotechworld.it/bioinf/2016/03/09/analyzing-fluoresence-microscopy-data-with-r/

data("leio_cells_dapi")
data("leio_cells_green")
dapi_mask <- get_dapi_range(leio_cells_dapi, 0.05)
leio_img <- leio_cells_green[500:1100, 700:1100]
d_mask <- dapi_mask[500:1100, 700:1100]
nc_signal <- apply_mask(leio_img, d_mask, bckgrnd = 0.05)
plot_signal(nc_signal)