bioimage

A Python-based tool for parallelized conversion of image datasets from various formats to OME-Zarr, with support for distributed processing and multi-dimensional concatenation.

A nextflow based tool that wraps bfconvert and bioformats2raw to convert image data collections to OME-TIFF and OME-Zarr, respectively, in a parallelised manner.

Clear multiscale image metadata manipulation in python

Course materials for the practical on the Defragmentation Training School 2 - Porto, 8-12 May 2023

Bio- and biomedical imaging dataset for machine learning and deep learning (for ExperimentHub in Bioconductor)

A lightweight library for lazy operations on Zarr arrays without task graph overhead

Jupyter Notebooks e codigos para analise de bioimagens e dados biologicos utilizados no meu canal BioPrograma - https://www.youtube.com/channel/UCbJAU7N9FYvwkdgSwD_1S4Q

Training website for the OME-Zarr format and the tooling around it.

Tired of counting cells by hand? 🔬 This project uses a U-Net deep learning model to automatically find and count cells, saving you time and improving accuracy. Perfect for researchers and bio-AI enthusiasts!

Fiji macros that batch-run temporal colour coding across all LUTs on a z-stack, with an optional reversed-order variant

Lazy, memory-bounded connected-components labeling for large N-dimensional arrays (interior-boundary reconciliation; dask output)

A specialized batch-processing pipeline for Zeiss CZI files. Optimized for ApoTome & Brain sections. Fixes hyperstack dimensions, recovers LUTs, and removes shading via rolling-ball pre-processing.

Lazy, memory-bounded connected-components labeling and per-object measurement for OME-Zarr pyramids