Common Workflow Language (CWL) Nuclear Segmentation worflow

CWL feature extraction workflow for imaging dataset

Workflow Steps:

create a Conda environment using python = ">=3.9,<3.12"

1. Install polus-plugins.

• clone a image-tools repository git clone https://github.com/camilovelezr/image-tools.git
• cd image-tools
• pip install .

2. Install workflow-inference-compiler.

• clone a workflow-inference-compiler repository git clone https://github.com/camilovelezr/workflow-inference-compiler.git
• cd workflow-inference-compiler
• pip install -e ".[all]"

Details

This workflow integrates seven distinct plugins, starting from data retrieval from Broad Bioimage Benchmark Collection, renaming files, correcting uneven illumination, segmenting nuclear objects.

Below are the specifics of the plugins employed in the workflow

1. bbbc-download-plugin
2. file-renaming-tool
3. ome-converter-tool
4. basic-flatfield-estimation-tool
5. apply-flatfield-tool
6. kaggle-nuclei-segmentation
7. polus-ftl-label-plugin

Execute CWL Segmentation workflow

The parameters for each imaging dataset are pre-defined and stored in JSON format. A Pydantic model in a utils Python file can be utilized to store parameters for any new dataset

python cwl_workflows/__main__.py --name="BBBC039" --workflow=segmentation

A directory named workflow is generated, encompassing CLTs for each plugin, YAML files, and all outputs are stored within the outdir directory.

workflows
├── experiment
│   └── cwl_adapters
|   experiment.cwl
|   experiment.yml
|
└── outdir
    └── experiment
        ├── step 1 BbbcDownload
        │   └── outDir
        │       └── bbbc.outDir
        │           └── BBBC
        │               └── BBBC039
        │                   └── raw
        │                       ├── Ground_Truth
        │                       │   ├── masks
        │                       │   └── metadata
        │                       └── Images
        │                           └── images
        ├── step 2 FileRenaming
        │   └── outDir
        │       └── rename.outDir
        ├── step 3 OmeConverter
        │   └── outDir
        │       └── ome_converter.outDir
        ├── step 4 BasicFlatfieldEstimation
        │   └── outDir
        │       └── estimate_flatfield.outDir
        ├── step 5 ApplyFlatfield
        │   └── outDir
        │       └── apply_flatfield.outDir
        ├── step 6 KaggleNucleiSegmentation
        │   └── outDir
        │       └── kaggle_nuclei_segmentation.outDir
        ├── step 7 FtlLabel
        │   └── outDir
        │       └── ftl_plugin.outDir