Published June 25, 2026 | Version v1
Dataset Open

Data and code associated with: napari-lattice: A user-friendly image processing tool for lattice light-sheet microscopy data

Authors/Creators

  • 1. Walter and Eliza Hall Institute of Medical Research
  • 2. EDMO icon The University of Melbourne
  • 3. ROR icon Aston University
  • 4. ROR icon University of Cape Town

Description

Neutrophil NETosis — lattice light-sheet imaging & analysis

Code and data accompanying the manuscript napari-lattice: A user-friendly image processing tool for lattice light-sheet microscopy data. The pipeline deskews and crops lattice light-sheet (LLS) timelapse data with napari-lattice, segments neutrophil nuclei with an ilastik pixel classifier, and extracts morphological/intensity measurements with scikit-image regionprops.

Record contents

File / archive Size Description
code.zip ~20 MB All code: environment spec, example notebooks, test data, and HPC pipeline scripts.
6h_timelapse-06(1).czi 35.1 GB Zeiss lattice light-sheet timelapse (6 h), SPY650-labelled neutrophil nuclei.
6h_timelapse-06(1)_MIP.czi 302 MB Max-intensity 2D projection of the raw LLS data.
6h_timelapse_1_ROIs.zip ~3 kB Fiji ROIs used to crop individual cells from the timelapse.
Supplementary_opm_data.zip 3.7 GB Two oblique-plane-microscopy datasets (raw + deskewed) showing the deskewing pipeline generalises beyond LLS.

Data structure

record/
├── README.md                          overview, install, and usage (start here)
├── code.zip
│   └── code/
│       ├── README.md                  copy of this overview
│       ├── environment.yml            conda/mamba environment spec
│       ├── data/                      empty; copy the raw .czi / ROIs here for the HPC pipeline
│       ├── examples/                  runnable demo (no cluster / raw data needed)
│       │   ├── test_entire_workflow.ipynb     end-to-end segmentation + measurement demo
│       │   ├── create_napari_workflow.ipynb   how the napari-workflows .yml is built
│       │   └── test_data/                      three small 3D crops (+ mask) and their README
│       └── hpc_scripts/               SLURM batch pipeline (run on a cluster)
│           ├── workflow/              segmentation function, ilastik classifier, workflow .yml
│           ├── crop_analysis/         deskew + crop + run the segmentation workflow
│           ├── crop_deskew_only/      deskew + crop only
│           ├── deskew_only/           deskew only
│           └── benchmarking/          runtime/scaling benchmarks (ROI vs full-FOV)
├── 6h_timelapse-06(1).czi             raw LLS timelapse
├── 6h_timelapse-06(1)_MIP.czi         max-intensity projection
├── 6h_timelapse_1_ROIs.zip            Fiji cropping ROIs
└── Supplementary_opm_data.zip
    ├── brain_organoid/                4×-expanded brain organoid, direct-view OPM (raw + deskewed + config)
    └── thy1_eGFP/                     Thy1-GFP mouse brain, scanned oblique plane (SOPi) (raw + deskewed + config)

Start with README.md.

Software: Python 3.10, ilastik-core 1.4.1, lls_core 1.2.1 (see environment.yml).

Files

6h_timelapse_1_ROIs.zip

Files (39.2 GB)

Name Size
md5:3660fc74fd6f9482d9ed11438cf022cd
35.1 GB Download
md5:573a35f3e0959870b549bd4567d90773
301.8 MB Download
md5:822d79e30997ff802c0c7f5980f108fc
3.2 kB Preview Download
md5:94c17c93f06b6fb16e8c1b3f6fc6faf1
19.6 MB Preview Download
md5:bc40779b7227ff6438d8ec9f67133de1
7.3 kB Preview Download
md5:35036d81886bfd2feeb0041445cc4d89
3.7 GB Preview Download

Additional details

Funding

Chan Zuckerberg Initiative (United States)
Napari Plugin Accelerator Grant 2021-240341
Chan Zuckerberg Initiative (United States)
Napari Plugin Accelerator Grant 2022-252520
International Human Frontier Science Program Organization
Career Development Award LT000213/2020-C
Research England

Software

Repository URL
https://github.com/BioimageAnalysisCoreWEHI/napari_lattice
Programming language
Python