MVRegFus

Multi-View Registration and Fusion

Python module to process multi-view light sheet data. This includes

1. Image registration

   • view registration
   • time registration (e.g. for drift correction)
   • channel registration (affine chromatic aberration correction)

2. View fusion

   • weighted additive fusion
   • multi-view deconvolution (Richardson-Lucy)
   • for both fusion types, weights can be:
     • blending weights
     • based on an image quality metric

• Additional features:

  • processing pipeline is leveraged by dask
    • entire workflow can be executed on laptops, independently of output dataset size (two input views need to fit into memory at once)
    • execution on computational clusters using dask.distributed
  • GPU accelerated multi-view deconvolution (using CuPy)

Notes:

• currently, (only) czi files from Z1 microscopes are supported out of the box

MVRegFus uses the elastix registration toolkit for performing most image registration.

Installation instructions

• clone this repository from github: git clone https://github.com/m-albert/MVRegFus.git

• use anaconda to install an environment from the provided .yml file: conda env create --file MVRegFus/mv_environment.yml

• install MVRegFus pip install -e ./MVRegFus

• Download elastix 4.9 (binary version 4.9 suitable for your platform) and place files into a folder 'elastix' next to the project folder, as such:

./MVRegFus
./MVRegFus/bin
...
./elastix
./elastix/bin
./elastix/lib

You're set!

Usage

• open terminal / anaconda prompt

• activate the previously installed anaconda environment: conda activate mvregfus (Win,MacOS) or source activate mvregfus (Linux)

• copy mvregfus/bin/mvregfus_bin.py to <your_mvregfus_bin.py> (can be placed next to data) and use as a template to indicate the location of your files, resolution, etc. (see comments in file). Soon configuration file handling will be added

• run fusion from the terminal with python <your_mvregfus_bin.py>

Dependencies

Python libraries:

• numpy, scipy
• h5py
• dask
• distributed
• dipy
• SimpleITK
• scikit-image
• bcolz
• tifffile (included)
• czifile==2019.1.26 (included)
• cupy (optional)

External:

• elastix
• SimpleElastix (optional)