# Description This repository contains the full data set for constructing the DAPI template, the full DAPI template creation pipeline and the automatic slice segmentation.
Program for automatic segmentation to a DAPI-stained coronal mouse brain slices.
Usage
python3 auto_seg.py sliceloc segloc templateloc --bregma [coord]
Positional/Required Arguments
sliceloc |
Location of the slice you wish to register (.nii or.nii.gz) |
segloc |
Location of file containing segmentation of the template (.nii or.nii.gz) |
templateloc |
Location of template file (.nii or .nii.gz) |
--bregma [coord] |
Bregma coordinate of input slice (if --approx argument is present, this is an optional argument) |
Optional arguments
--approx [index] |
Provide the location of the slice as a z-index of the template. Can be used instead of --bregma argument. |
--out [directory] |
Provide an alternative output directory (default directory is /output) |
--dapi [index] |
Index of the DAPI channel in the slice, by default the DAPI channel is assumed to be the last channel |
Usage
python3 preprocess.py file dir -s Series -b [True/False] --pdim [pixeldimension]
Positional/Required Arguments
file |
Location of the file to be preprocessed (.tiff or .nd2) |
dir |
Directory to output preprocessed files (will output .nii files) |
-s |
The series to extract (If input file is single-series, use 0 for this argument) |
Optional arguments
--b [True/False] |
Bias field correction: Whether to use bias-field correction in preprocessing (default: True) |
--pdim [pixeldimensions] |
Dimensions of pixels, if not provided, these will be extracted from image metadata |