What problem does it solve?
OMERO integration removes the manual bottlenecks of browsing, retrieving, annotating, and analyzing microscopy images by providing programmatic access to OMERO projects, datasets, images, ROIs, and associated measurement outputs.
Core Features & Use Cases
- OMERO session & context management: connect to an OMERO server with robust session lifecycle handling and group-based access context.
- Hierarchical data retrieval: navigate Project → Dataset → Image, and screening hierarchies (Screen → Plate → Well → WellSample → Image) to fetch exactly the objects you need.
- Microscopy pixel access & image analysis hooks: access raw pixel planes/tiles as NumPy arrays, compute derived images (e.g., projections), and support rendering thumbnails.
- ROI and annotation workflows: create and manage ROIs (rectangles, ellipses, polygons, masks, points, lines), add structured metadata via tags/map/file annotations, and store measurements as OMERO tables.
- Batch processing & server-side automation: run batch workflows via OMERO.scripts for high-throughput screening and repeated analysis pipelines.
Use Case: You have a high-content screening experiment with many images; use this skill to batch-retrieve images, compute ROI intensity statistics, attach results back to OMERO as tables, and maintain ROIs/annotations for downstream review.
Quick Start
Connect with OMERO’s BlitzGateway in Python, retrieve the target Image(s), and then create or analyze ROIs using the ROI service while optionally saving measurements to OMERO tables.
