README.md

metadata

title: WaveOrder
emoji: 🔬
python_version: 3.13
colorFrom: blue
colorTo: purple
sdk: gradio
sdk_version: 6.0.2
app_file: app.py
pinned: false
license: bsd-3-clause
tags:
  - microscopy
  - computational-imaging
  - phase-reconstruction
  - bioimaging
  - scientific-visualization

WaveOrder

📄 Paper

WaveOrder: generalist framework for label-agnostic computational microscopy Chandler T., Ivanov I.E., Hirata-Miyasaki E., et al. "WaveOrder: Physics-informed ML for auto-tuned multi-contrast computational microscopy from cells to organisms." arXiv:2412.09775 (2025)

🔬 About

Interactive web interface for exploring phase reconstruction from quantitative label-free microscopy data. This demo showcases the WaveOrder framework's capabilities for reconstructing phase contrast images with interactive parameter optimization.

Features

• Interactive Visualization: Side-by-side comparison of raw and reconstructed phase images
• Real-time Parameter Tuning: Adjust reconstruction parameters and see results instantly
• Automated Optimization: Gradient-based optimization to find optimal reconstruction parameters
• GPU Acceleration: 15-25× speedup with CUDA-capable devices (auto-detected)
• Multi-FOV Support: Navigate through multiple fields of view from plate imaging

Reconstruction Parameters

• Z Offset: Axial focus calibration
• Numerical Apertures: Detection and illumination NA optimization
• Tilt Angles: Zenith and azimuthal illumination tilt correction

🚀 Usage

1. Select Field of View: Choose from available FOVs in the dropdown
2. Navigate Z-stack: Use the Z-slice slider to explore different focal planes
3. Optimize Parameters: Click "⚡ Optimize Parameters" to automatically find optimal settings
4. Manual Reconstruction: Adjust sliders manually and click "🔬 Run Reconstruction"
5. Review Results: Scrub through optimization iterations to see parameter evolution

📊 Dataset

This demo uses concatenated 20x objective microscopy data from high-content screening plates, featuring brightfield phase contrast imaging.

🔗 Links

• Paper: arXiv:2412.09775
• GitHub Repository: mehta-lab/waveorder
• Documentation: WaveOrder Docs

📝 Citation

@misc{chandler2024waveordergeneralistframeworklabelagnostic,
      title={waveOrder: generalist framework for label-agnostic computational microscopy},
      author={Talon Chandler and Eduardo Hirata-Miyasaki and Ivan E. Ivanov and Ziwen Liu and Deepika Sundarraman and Allyson Quinn Ryan and Adrian Jacobo and Keir Balla and Shalin B. Mehta},
      year={2024},
      eprint={2412.09775},
      archivePrefix={arXiv},
      primaryClass={physics.optics},
      url={https://arxiv.org/abs/2412.09775},
}

⚖️ License

BSD 3-Clause License