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TPR4Py is a tool to recover quantitative phase differences from a 3D stack of Koehler illuminated bright field images. It is based on the Matlab script from https://c4science.ch/source/TomPhaseRet/

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GrussmayerLab/TPR4Py

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TomographicPhaseRetrieval for Python - TPR4Py

TPR4Py is a tool to recover quantitative phase differences from a 3D stack of bright field images. It is based on the Matlab script from https://c4science.ch/source/TomPhaseRet/ further described in:

Descloux, A., Grußmayer, K.S., Bostan, E. et al. Combined multi-plane phase retrieval and super-resolution optical fluctuation imaging for 4D cell microscopy. Nature Photon 12, 165–172 (2018). https://doi.org/10.1038/s41566-018-0109-4

The main script contains a basic pipeline for quantitative phase retrieval from brightfield stacks

  • 3D image stack loading
  • 3D stack preprocessing
  • processing parameters definition
  • phase calculation
  • display of the results (optional, conducted via napari)

Installation

Via command line:

git clone git@github.com:GrussmayerLab/TomographicPhaseRetrieval.git

clones into the repository and gives access to the source code on your local machine

Ideally a separate environment is set up and dependencies installed. This can be done by via the environment.yml file:

conda env create -f environment.yml 

Processing only

pip install -r requirements.txt 

This basically sets up the necessary scikit-image and numpy modules. Visualisation with napari is not possible with these modules.

Visualisation included

To display the 3D phase map, install napari into your local virtual environment via

python -m pip install "napari[all]"

This initialises napari version 0.4.12 that enables a powerful n-dimensional image processing and visualisation toolbox. Please refer to the napari github for further instructions: https://napari.org/index.html If you set up a virtual environment via the environment.yml file, this step might well be unnecessary.

Requirements

The functionality has been tested on following versions. Compatibility with older versions is not ensured but should be be possible.

  • sci-kit image == 0.19.2
  • numpy == 1.12.5
  • (napari == 0.4.12 -> only necessary when you want to view the 3D phase map in the viewer)

Usage

  • qp_main.py is the main script that can be run in the IDE of choice. It accesses the utility scripts under /utils.

input

A .tiff or .png stack containing at least two z-positions of the investigated object.

returns 'QP'

A 3D stack with the same dimensions as the input image stack, wherein each pixel represents the rad-pathlength differences.

Contributing

A detailled description of the theory supporting this program can be found in : "Descloux, A., et al. "Combined multi-plane phase retrieval and super-resolution optical fluctuation imaging for 4D cell microscopy." Nature Photonics 12.3 (2018): 165. The script was originally designed by the authors in matlab. The adaption to python 3 was conducted by Moritz Engelhardt, Grussmayer Lab TU Delft (2022).

License

Copyright © 2018 Adrien Descloux - adrien.descloux@epfl.ch, École Polytechnique Fédérale de Lausanne, LBEN/LOB, BM 5.134, Station 17, 1015 Lausanne, Switzerland.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

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TPR4Py is a tool to recover quantitative phase differences from a 3D stack of Koehler illuminated bright field images. It is based on the Matlab script from https://c4science.ch/source/TomPhaseRet/

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