bioimaging

Next-generation file format (NGFF) specifications for storing bioimaging data in the cloud.

Compile and explore arbitrarily large n-dimensional scientific data in the browser — points, lines, Gaussian splats and meshes, streamed from Zarr and rendered on the GPU.

A WebGPU-native out-of-core rendering system for large virtualized volumetric data.

C++ library and command-line software for processing and analysis of terabyte-scale volume images locally or on a computing cluster.

Pythonic and parallelizable I/O for N-dimensional imaging data with OME metadata

Discover, install, and share napari plugins

Python libraries for loading, running and packaging bioimage.io models

SIMPLI is a highly configurable pipeline for the analysis of multiplexed imaging data.

R package for visualization of highly multiplexed imaging data

BIOMERO.analyzer - A python library for easy connecting between OMERO (jobs) and a Slurm cluster

A web-based resource for the scientific visualization community to enhance reproducibility and facilitate testing and development of OME-Zarr tools.

An introduction to OME-Zarr for big bioimaging data

Package providing bioimaging functionality using TileDB. Source of the tiledb-bioimg Python package.

Python 3 x-ray simulator

High-performance, IBSI-compliant radiomics feature extraction in Julia, running seamlessly on CPU and GPU

DeepCOVIDExplainer: Explainable COVID-19 Diagnosis from Chest X-ray Images

TileDB BioImaging plugin for Napari

Dataset- and model-agnostic tool for phenotyping analysis using deep learning embeddings and image properties.

Visualisation software for imaging mass cytometry data

3D volume rendering software for fluorescence microscopy