annotatR: Multi-Layer Region-of-Interest Annotation for Images and Spectral Cubes

Annotate multiple layers of regions of interest across whole-slide microscopy images, hyperspectral data cubes, and conventional rasters. Annotations are stored as validated simple-feature geometries in image pixel coordinates with explicit pyramid-level transforms, and can be rasterised to binary, labelled, or multi-class integer masks for downstream segmentation and classification workflows. A batch annotation application built on 'shiny' and 'OpenSeadragon' supports resumable sessions across image queues, live mask preview, and export to 'GeoJSON', 'QuPath', and 'TIFF' formats.

See also

Useful links:

• https://github.com/CTTIR/annotatR

• https://cttir.github.io/annotatR/

• Report bugs at https://github.com/CTTIR/annotatR/issues

Author

Maintainer: Raban Heller raban.heller@charite.de (ORCID)

Authors:

• Raban Heller raban.heller@charite.de (ORCID)