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README.md

Output

Running the runner.py will yield the following outputs.

  • A nifti file of the pre-processed input slice, called [outputdir]/[name].nii
  • A directory with the same name as the input slice, [outputdir]/[name]/ in which you will find the following outputs
    • The different channels of the input slice ('im_c1.nii', 'im_c2.nii, ...')
    • The segmentation of the input file in pre-processed space, called Segmentation.nii (Can be viewed in ITK-SNAP by opening one of the channels as main image and the 'Segmentation.nii' as segmentation)
    • The DAPI template slice registered to the input slice, called TemplateSlice__InverseWarped.nii.gz
    • The input slice registered registered to the DAPI template slice, called im_c[dapi_index]_template.nii
    • The composite transformation of the input slice to the corresponding template slice, called 'Transformation_Composite.h5'
    • The inverse composite transformation, i.e. the transformation from the template slice to the input slice, called 'Transformation_InverseComposite.h5'

Parameters

Detailed parameter description. For example see ../Example/runner_example.sh

Usage

python3 runner.py sliceloc segloc templateloc bregma outputdir

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
outputdir Location for the output of the registration files

Optional arguments

--dapi [index] Index of the DAPI channel in the slice, by default the DAPI channel is assumed to be the last channel
datacite.yml
Title A three-dimensional, population-based average of the C57BL/6 mouse brain from DAPI-stained coronal slices
Authors Stæger,Frederik Filip;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark;ORCID:0000-0002-2295-8637
Mortensen,Kristian;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark;ORCID:0000-0003-3726-0781
Nielsen,Malthe Skytte Nordentoft;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark;ORCID:0000-0002-7833-5877
Hirase,Hajime;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark;ORCID:0000-0003-3806-6905
Sigurdsson,Björn;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark;ORCID:0000-0002-7484-7779
Kaufmann,Louis;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
Nedergaard,Maiken;Center for Translational Neuromedicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark and Center for Translational Neuromedicine, University of Rochester Medical Center, Rochester, NY 14642, USA.;ORCID:0000-0001-6502-6031
Description The full data set and pipeline for constructing the three-dimensional, population-based average of the C57BL/6 mouse brain form DAPI-stained coronal slices. This repository also contains a python implementation of automatic coronal brain slice segmentation. The data set constitutes of all the raw slice images (.tif) in full resolution, the pre-processed version (.nii), the individually reconstructed brain volumes, and the final population-based average.
License Creative Commons CC0 1.0 Public Domain Dedication (https://creativecommons.org/publicdomain/zero/1.0/)
References A three-dimensional, population-based average of the C57BL/6 mouse brain from DAPI-stained coronal slices [] (IsDescribedBy)
Funding
Keywords Neuroscience
Mouse brain template
C57BL/6 brain template
DAPI
Population-based average
Automatic segementation
Resource Type Dataset