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-# DAPI template pipeline
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-The original pipeline for pre-processing, reconstructing, and template
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-creation of the DAPI template.
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-
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-## Description
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-The reconstruction and template creation was run twice.
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-First with the allen reference atlas as reference without non-linear
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-registration steps resulting in an initial DAPI template. The initial DAPI
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-template was used as reference (instead of the Allen reference atlas)
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-in the second run of reconstruction and template creation, resulting in the
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-final DAPI template. The two runs of the pipeline were manually modified.
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-
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-This pipeline is based on the original data structure of the slice images
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-with a few sanity checks to make sure that all images are present. To run this
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-pipeline with the data structure from the GIN-repository you need to remove
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-these sanity checks, get the mouse ids from a different directory (like tif/),
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-and get all the image paths in each individual tif folder.
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-
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-## Overview
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-The main script calls the pre_processing, co_registration, and
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-template_creation with appropriate parameters and paths. In pre_processing
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-the original tif image is down-sampled to 8.6x8.6 um and masked according to
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-the biggest (except background) connected component after smoothing and
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-threshold to remove artefact outside of the brain slice.
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-After pre-processing the slices for each brain is reconstructed
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-into 3-dimensional brain volumes. This reconstruction is carried out by
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-iterative registrations (both between volumes and between slice-pairs) to
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-a reference (Allen or DAPI from first iteration). Finally, each reconstructed
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-brain volume is used in the creation of a population-based average in
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-template_creation.
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-
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-## Packages
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-This pipeline uses the following non-standard packages (package name: version):
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-
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-```
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-nibabel: 2.1.0
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-nipype: 0.13.1
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-numpy: 1.15.1
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-PIL: 5.1.0
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-scipy: 1.1.0
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-skimage: 0.14.0
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-sklearn: 0.19.2
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-```
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-
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-## Registration software
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-A precompiled binary of Advanced Normalization Tools (ANTs) V.2.1.0 for
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-linux/mac was used.
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