README.md 2.5 KB

Description

This repository contains the full data set for constructing the DAPI template, the full DAPI template creation pipeline and the automatic slice segmentation.

Automatic slice segmentation

Program for automatic segmentation to a DAPI-stained coronal mouse brain slices.

Dependencies

Prerequisites

  • A high-resolution, DAPI modality TIFF image of a brain slice. Can have multiple channels.
  • A template file (.nii or .nii.gz)
  • A segmentation of the template file (.nii or .nii.gz)

Usage

  • Use preprocess.py to prepare input slice for automatic registration
  • Use auto_seg.py with preprocessed slice which will output a folder containing segmentation registered to slice.

Details

Detailed parameter description.

auto_seg.py

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

preprocess.py

Usage

python3 preprocess.py file dir -s Series --pdim [pixeldimensions]  

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

--pdim [pixeldimensions] Dimensions of pixels, if not provided, these will be extracted from image metadata