dynacell.yaml

Name: DynaCell
Description: |
  DynaCell is an evaluation framework for dynamic 3D virtual staining of live cells.
  The dataset pairs label-free transmitted-light volumes (phase reconstructions from brightfield z-stacks) with fluorescence ground truth for four organelles (nucleus, cell membrane,
  endoplasmic reticulum, mitochondria) across three conditions
  (uninfected, Zika-infected, Dengue-infected).

  The v1 release contains images of A549 human lung adenocarcinoma cells acquired on
  the Mantis correlative label-free and light-sheet fluorescence microscope at Biohub
  (24 OZX stores, 262 FOVs, ~407 GB), split into train and test sets across 4 organelle
  markers and 3 conditions.

  A v1.1 release will add the WTC-11 hiPSC component: cells from the Allen Institute
  hiPSC single-cell image dataset (Viana et al., Nature 2023), reprocessed as paired
  label-free and confocal fluorescence volumes. The iPSC dataset is redistributed under
  the Allen Institute Terms of Use (https://www.allencell.org/terms-of-use.html), which
  requires citation of the original dataset and limits use to noncommercial research.

  All data are stored as RFC-9 zipped OME-Zarr (.ozx) archives following OME-NGFF v0.5,
  readable with iohub (https://github.com/czbiohub-sf/iohub). Machine-readable metadata
  (Croissant JSON-LD with Responsible AI fields, per the NeurIPS Datasets & Benchmarks
  track) is published at s3://dynacell/v1/metadata/croissant.json.
Documentation: https://github.com/mehta-lab/VisCy/tree/modular-viscy-staging/applications/dynacell
Contact: shalin.mehta@biohub.org
ManagedBy: "[Biohub](https://www.biohub.org/)"
UpdateFrequency: As needed - v1 (A549) is frozen; future releases will expand the dataset.
Tags:
  - aws-pds
  - biology
  - image-based profiling
  - cell biology
  - life sciences
  - cell imaging
  - fluorescence imaging
  - microscopy
  - machine learning
  - benchmark
  - computer vision
  - zarr
License: "[CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)"
RegistryEntryAdded: "2026-05-04"
RegistryEntryLastModified: "2026-05-04"
Resources:
  - Description: |
      DynaCell v1 release: paired label-free and fluorescence 3D+time volumes
      in RFC-9 zipped OME-Zarr (.ozx) format. Contains biohub-a549 (train/test
      splits, 4 markers x 3 conditions = 24 stores), Croissant 1.1 metadata
      with Responsible AI fields, and placeholders for forthcoming demo
      samples, trained model checkpoints, and supplementary movies.
    ARN: arn:aws:s3:::dynacell
    Region: us-west-2
    Type: S3 Bucket
DataAtWork:
  Tutorials:
  Tools & Applications:
    - Title: VisCy — training, prediction, and evaluation pipelines for DynaCell
      URL: https://github.com/mehta-lab/VisCy/tree/modular-viscy-staging/applications/dynacell
      AuthorName: Computational Imaging Group at Biohub
      AuthorURL: https://www.biohub.org/comp-micro
    - Title: iohub — OME-Zarr and OZX I/O library
      URL: https://github.com/czbiohub-sf/iohub
      AuthorName: Computational Imaging Group at Biohub
      AuthorURL: https://www.biohub.org/comp-micro
    - Title: waveorder — phase reconstruction from label-free microscopy
      URL: https://github.com/mehta-lab/waveorder
      AuthorName: Computational Imaging Group at Biohub
      AuthorURL: https://www.biohub.org/comp-micro
  Publications:
    - Title: "DynaCell: an Evaluation Framework for Dynamic 3D Virtual Staining of Live Cells"
      URL: https://github.com/mehta-lab/VisCy/tree/modular-viscy-staging/applications/dynacell
      AuthorName: Kalinin, Zheng, Theodoro, Ivanov, Hirata-Miyasaki, Lee, Liu, Varra, Chandler, Pradeep, Liu, Leonetti, Arias, Huang, Mehta
      AuthorURL: https://www.biohub.org/comp-micro