Research Object Crate for Load ome.zarr Image with labels from a public S3 repository, analyze using StarDist and compare results

Original URL: https://workflowhub.eu/workflows/496/ro_crate?version=1

The image is referenced in the paper "NesSys: a novel method for accurate nuclear segmentation in 3D" published August 2019 in PLOS Biology: https://doi.org/10.1371/journal.pbio.3000388 and can be viewed online in the [Image Data Resource](https://idr.openmicroscopy.org/webclient/?show=image-6001247). This original image was converted into the Zarr format. The analysis results produced by the authors of the paper were converted into labels and linked to the Zarr file which was placed into a public S3 repository. In this notebook, the Zarr file is then loaded together with the labels from the S3 storage and analyzed using [StarDist](https://github.com/stardist/stardist). The StarDist analysis produces a segmentation, which is then viewed side-by-side with the original segmentations produced by the authors of the paper obtained via the loaded labels. ## Launch This notebook uses the [environment_stardist.yml](https://github.com/ome/EMBL-EBI-imaging-course-05-2023/blob/main/Day_5/environment_stardist.yml) file. See [Setup](https://github.com/ome/EMBL-EBI-imaging-course-05-2023/blob/main/Day_5/setup.md).

Author
Jean-Marie Burel
License
BSD-2-Clause

Contents

Main Workflow Diagram: StarDistNgff.png
Size: 689789 bytes