Steinbock Results: Processed Imaging Mass Cytometry Example Data

Processed results from example imaging mass cytometry (IMC) data using the Steinbock framework. The repository includes multi-channel images, segmentation masks, and single-cell measurements of intensity, morphology, and spatial neighbors. Nils Eling from the University of Zurich authored this processed dataset.

Use Cases

• Benchmarking cell segmentation algorithms based on the provided ilastik and DeepCell masks.
• Analyzing single-cell protein expression patterns based on mean pixel intensity measurements per channel.
• Studying cell morphology and spatial relationships using region property and neighbor edge list data.
• Training or validating pixel classifiers for IMC data using the provided ilastik classifier and image crops.

Strengths

• Includes multiple processed data types: raw images, segmentation masks, and single-cell measurements.
• Provides outputs from two distinct segmentation methods (ilastik and DeepCell) for comparison.
• Data is formatted for compatibility with specific analysis tools like histoCAT and AnnData.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Row count and dataset scale are unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.

Provenance

Source

University of Zurich, Bodenmiller Group

Collection Method

Processed from raw IMC data hosted on Zenodo using the Steinbock framework.