waveorder

Wave optical models and inverse algorithms for label-agnostic imaging of density & orientation.

https://github.com/mehta-lab/waveorder

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 9 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
    3 of 15 committers (20.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (13.2%) to scientific vocabulary

Keywords

label-free mipolscope optics permittivity permittivity-tensor-imaging phase polarization qlipp reconstruction-algorithm scattering simulation
Last synced: 6 months ago · JSON representation

Repository

Wave optical models and inverse algorithms for label-agnostic imaging of density & orientation.

Basic Info
Statistics
  • Stars: 30
  • Watchers: 5
  • Forks: 6
  • Open Issues: 73
  • Releases: 8
Topics
label-free mipolscope optics permittivity permittivity-tensor-imaging phase polarization qlipp reconstruction-algorithm scattering simulation
Created about 5 years ago · Last pushed 6 months ago
Metadata Files
Readme Contributing License Citation

README.md

Image

Python package index PyPI monthly downloads Total downloads GitHub contributors GitHub Repo stars GitHub forks PyPI - Python Version

Label-agnostic computational microscopy of architectural order.

Overview

waveorder is a generalist framework for label-agnostic computational microscopy of architectural order, i.e., density, alignment, and orientation of biomolecules with the spatial resolution down to the diffraction limit. The framework implements wave-optical simulations and corresponding reconstruction algorithms for diverse label-free and fluorescence computational imaging methods that enable quantitative imaging of the architecture of dynamic cell systems.

Our goal is to enable modular and user-friendly implementations of computational microscopy methods for dynamic imaging across the scales of organelles, cells, and tissues.

The framework is described in the following preprint.

https://github.com/user-attachments/assets/4f9969e5-94ce-4e08-9f30-68314a905db6

`waveorder` enables simulations and reconstructions of label-agnostic microscopy data as described in the following [preprint](https://arxiv.org/abs/2412.09775) Chandler et al. 2024

@article{chandler_2024,
    author = {Chandler, Talon and Hirata-Miyasaki, Eduardo and Ivanov, Ivan E. and Liu, Ziwen and Sundarraman, Deepika and Ryan, Allyson Quinn and Jacobo, Adrian and Balla, Keir and Mehta, Shalin B.},
    title = {waveOrder: generalist framework for label-agnostic computational microscopy},
    journal = {arXiv},
    year = {2024},
    month = dec,
    eprint = {2412.09775},
    doi = {10.48550/arXiv.2412.09775}
}

Computational Microscopy Methods

waveorder framework enables simulations and reconstructions of data for diverse one-photon (single-scattering based) computational microscopy methods, summarized below.

Label-free microscopy

Quantitative label-free imaging with phase and polarization (QLIPP)

Acquisition, calibration, background correction, reconstruction, and applications of QLIPP are described in the following E-Life Paper:

Unveiling the invisible

Guo et al. 2020

@article{guo_2020,
    author = {Guo, Syuan-Ming and Yeh, Li-Hao and Folkesson, Jenny and Ivanov, Ivan E. and Krishnan, Anitha P. and Keefe, Matthew G. and Hashemi, Ezzat and Shin, David and Chhun, Bryant B. and Cho, Nathan H. and Leonetti, Manuel D. and Han, May H. and Nowakowski, Tomasz J. and Mehta, Shalin B.},
    title = {Revealing architectural order with quantitative label-free imaging and deep learning},
    journal = {eLife},
    volume = {9},
    pages = {e55502},
    year = {2020},
    doi = {10.7554/eLife.55502}
}

Permittivity tensor imaging (PTI)

PTI provides volumetric reconstructions of mean permittivity ($\propto$ material density), differential permittivity ($\propto$ material anisotropy), 3D orientation, and optic sign. The following figure summarizes PTI acquisition and reconstruction with a small optical section of the mouse brain tissue:

Data_flow

The acquisition, calibration, background correction, reconstruction, and applications of PTI are described in the following paper published in Nature Methods:

Yeh et al. 2024

@article{yeh_2024,
    author = {Yeh, Li-Hao and Ivanov, Ivan E. and Chandler, Talon and Byrum, Janie R. and Chhun, Bryant B. and Guo, Syuan-Ming and Foltz, Cameron and Hashemi, Ezzat and Perez-Bermejo, Juan A. and Wang, Huijun and Yu, Yanhao and Kazansky, Peter G. and Conklin, Bruce R. and Han, May H. and Mehta, Shalin B.},
    title = {Permittivity tensor imaging: modular label-free imaging of 3D dry mass and 3D orientation at high resolution},
    journal = {Nature Methods},
    volume = {21},
    number = {7},
    pages = {1257--1274},
    year = {2024},
    month = jul,
    issn = {1548-7105},
    publisher = {Nature Publishing Group},
    doi = {10.1038/s41592-024-02291-w}
}

Quantitative phase imaging (QPI) from defocus

phase from a volumetric brightfield acquisition (2D phase/3D phase)

Image

Jenkins and Gaylord 2015 (2D QPI from defocus)

    @article{Jenkins:15,
    author = {Micah H. Jenkins and Thomas K. Gaylord},
    journal = {Appl. Opt.},
    keywords = {Phase retrieval; Partial coherence in imaging; Interferometric imaging ; Imaging systems; Microlens arrays; Optical transfer functions; Phase contrast; Spatial resolution; Three dimensional imaging},
    number = {28},
    pages = {8566--8579},
    publisher = {Optica Publishing Group},
    title = {Quantitative phase microscopy via optimized inversion of the phase optical transfer function},
    volume = {54},
    month = {Oct},
    year = {2015},
    url = {https://opg.optica.org/ao/abstract.cfm?URI=ao-54-28-8566},
    doi = {10.1364/AO.54.008566},
}
Soto, Rodrigo, and Alieva 2018 (3D QPI from defocus)

@article{Soto:18,
author = {Juan M. Soto and Jos\'{e} A. Rodrigo and Tatiana Alieva},
journal = {Appl. Opt.},
keywords = {Coherence and statistical optics; Image reconstruction techniques; Optical transfer functions; Optical inspection; Three-dimensional microscopy; Acoustooptic modulators; Illumination design; Inverse design; LED sources; Three dimensional imaging; Three dimensional reconstruction},
number = {1},
pages = {A205--A214},
publisher = {Optica Publishing Group},
title = {Optical diffraction tomography with fully and partially coherent illumination in high numerical aperture label-free microscopy \[Invited\]},
volume = {57},
month = {Jan},
year = {2018},
url = {https://opg.optica.org/ao/abstract.cfm?URI=ao-57-1-A205},
doi = {10.1364/AO.57.00A205},
}

QPI with differential phase contrast

phase from differential phase contrast

Work in progress

Fluorescence microscopy

Widefield deconvolution microscopy

fluorescence density from a widefield volumetric fluorescence acquisition.

Swedlow 2013

@article{Swedlow:13,
author = {Swedlow, John R.},
journal = {Methods Cell Biol.},
title = {Quantitative fluorescence microscopy and image deconvolution},
year = {2013},
volume = {114},
pages = {407--26},
doi = {10.1016/B978-0-12-407761-4.00017-8}
}

Oblique plane light-sheet microscopy

fluorescence density from oblique plane light-sheet microscopy.

Ivanov, Hirata-Miyasaki, Chandler et al. 2024

@article{ivanov_2024,
author = {Ivanov, Ivan E. and Hirata-Miyasaki, Eduardo and Chandler, Talon and Cheloor-Kovilakam, Rasmi and Liu, Ziwen and Pradeep, Soorya and Liu, Chad and Bhave, Madhura and Khadka, Sudip and Arias, Carolina and Leonetti, Manuel D. and Huang, Bo and Mehta, Shalin B.},
title = {Mantis: High-throughput 4D imaging and analysis of the molecular and physical architecture of cells},
journal = {PNAS Nexus},
volume = {3},
number = {9},
pages = {pgae323},
year = {2024},
doi = {10.1093/pnasnexus/pgae323}

Citation

Please cite this repository, along with the relevant publications and preprints, if you use or adapt this code. The citation information can be found by clicking "Cite this repository" button in the About section in the right sidebar.

Installation

Create a virtual environment:

sh conda create -y -n waveorder python=3.12 conda activate waveorder

(Option 1) If you are familiar with waveorder's API and want to use it as a library, install a stable version of waveorder from PyPI:

sh pip install waveorder

(Option 2) If you are new to waveorder and want to run demos to become familiar with its features, install the latest version of waveorder from GitHub with all visualization dependencies (napari, jupyter), clone the repository, and run an example script: sh pip install "git+https://github.com/mehta-lab/waveorder.git@main#egg=waveorder[all]" git clone https://github.com/mehta-lab/waveorder.git python waveorder/docs/examples/models/phase_thick_3d.py

(M1 users) pytorch has incomplete GPU support, so please use export PYTORCH_ENABLE_MPS_FALLBACK=1 to allow some operators to fallback to CPU if you plan to use GPU acceleration for polarization reconstruction.

Examples

The examples illustrate simulations and reconstruction for 2D QLIPP, 3D phase from brightfield, and 2D/3D PTI methods.

Owner

  • Name: Computational Microscopy Platform (Mehta Lab), CZ Biohub
  • Login: mehta-lab
  • Kind: organization
  • Location: United States of America

GitHub Events

Total
  • Create event: 34
  • Release event: 3
  • Issues event: 266
  • Watch event: 13
  • Delete event: 14
  • Member event: 3
  • Issue comment event: 88
  • Push event: 191
  • Pull request review comment event: 135
  • Pull request review event: 160
  • Pull request event: 52
  • Fork event: 1
Last Year
  • Create event: 34
  • Release event: 3
  • Issues event: 266
  • Watch event: 13
  • Delete event: 14
  • Member event: 3
  • Issue comment event: 88
  • Push event: 191
  • Pull request review comment event: 135
  • Pull request review event: 160
  • Pull request event: 52
  • Fork event: 1

Committers

Last synced: about 2 years ago

All Time
  • Total Commits: 410
  • Total Committers: 15
  • Avg Commits per committer: 27.333
  • Development Distribution Score (DDS): 0.656
Past Year
  • Commits: 19
  • Committers: 3
  • Avg Commits per committer: 6.333
  • Development Distribution Score (DDS): 0.158
Top Committers
Name Email Commits
camfoltz c****2@g****m 141
lihaoyeh r****1@g****m 76
Bryant b****n@g****m 73
Ivan Ivanov i****v@c****g 40
Talon Chandler t****r@g****m 37
Shalin Mehta s****a@c****g 10
andrewdchen a****n@b****u 9
ieivanov i****v@s****u 7
Shalin Mehta 2****t 6
AndrewChen a****n@b****u 4
Johanna Rahm j****m@g****e 2
Ziwen Liu 6****u 2
Li-Hao Yeh l****h@m****l 1
Andrew Chen 3****n 1
Tiffany Chien t****n 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 313
  • Total pull requests: 163
  • Average time to close issues: 3 months
  • Average time to close pull requests: 18 days
  • Total issue authors: 18
  • Total pull request authors: 14
  • Average comments per issue: 2.27
  • Average comments per pull request: 1.26
  • Merged pull requests: 132
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 28
  • Pull requests: 55
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 16 days
  • Issue authors: 6
  • Pull request authors: 8
  • Average comments per issue: 1.43
  • Average comments per pull request: 1.33
  • Merged pull requests: 36
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • talonchandler (129)
  • ziw-liu (42)
  • ieivanov (40)
  • mattersoflight (39)
  • camFoltz (24)
  • edyoshikun (9)
  • bryantChhun (8)
  • JohannaRahm (6)
  • goanpeca (3)
  • amitabhverma (3)
  • Soorya19Pradeep (3)
  • dsundarraman (1)
  • aaronalvarezcz (1)
  • dbcortes2042000 (1)
  • alishbaimran (1)
Pull Request Authors
  • talonchandler (87)
  • camFoltz (16)
  • ziw-liu (15)
  • lihaoyeh (12)
  • ieivanov (10)
  • mattersoflight (6)
  • edyoshikun (6)
  • tayllatheodoro (2)
  • bryantChhun (2)
  • JohannaRahm (2)
  • ahillsley (2)
  • amitabhverma (1)
  • tiffchien (1)
  • Soorya19Pradeep (1)
Top Labels
Issue Labels
enhancement (36) bug (33) documentation (10) question (4) meta (3) help wanted (1) GPU (1)
Pull Request Labels
enhancement (7) bug (6) GPU (3) documentation (1)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 210 last-month
  • Total dependent packages: 2
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 21
  • Total maintainers: 2
pypi.org: waveorder

Wave-optical simulations and deconvolution of optical properties

  • Homepage: https://github.com/mehta-lab/waveorder
  • Documentation: https://waveorder.readthedocs.io/
  • License: BSD 3-Clause License Copyright (c) 2019, Chan Zuckerberg Biohub Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  • Latest release: 2.2.1
    published 11 months ago
  • Versions: 19
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 210 Last month
Rankings
Dependent packages count: 3.2%
Downloads: 10.5%
Average: 14.3%
Forks count: 16.9%
Stargazers count: 18.5%
Dependent repos count: 22.1%
Maintainers (2)
Last synced: 6 months ago
conda-forge.org: waveorder
  • Versions: 2
  • Dependent Packages: 1
  • Dependent Repositories: 0
Rankings
Dependent packages count: 28.8%
Dependent repos count: 34.0%
Average: 42.6%
Stargazers count: 53.5%
Forks count: 54.2%
Last synced: 6 months ago

Dependencies

.github/workflows/pytests.yml actions
  • actions/checkout v2 composite
  • actions/setup-python v1 composite
pyproject.toml pypi
setup.py pypi