cellpose

Omnipose: a high-precision solution for morphology-independent cell segmentation

Encoder-Decoder Cell and Nuclei segmentation models

an extension that wraps a Cellpose environment such that WSI can be analyzed using Cellpose through QuPath.

ImageJ macro for the analysis of foci (e.g. DNA damage) in nuclei/cells

Automated batch processing of cell and tissue microscopy image data in Napari

Large-scale cell segmentation with cellpose.

Fiji plugin to use Cellpose with Appose

BioEngine is a distributed AI platform that brings the power of cloud computing to bioimage analysis.

napari plugin for cellpose and Cellpose-SAM segmentation

Single cell resolution 3D imaging and segmentation within intact live tissues

Comprehensive pipeline for cell segmentation, tracking, and correlation analysis in time-lapse microscopy data. Utilizes deep learning models (Cellpose) for segmentation, with integrated refinement, tracking, and correlation analysis of dynamic cellular behaviors. Developed as part of a Master’s thesis project at KTH Royal Institute of Technology.

Graphical tool for creating image segmentation annotations and training custom Cellpose models

Mammary cell shape computation over time with Trackmate-Cellpose

MIC-MAQ for Microscopy Images of Cells - Multi Analyses and Quantifications is an ImageJ/Fiji Plugin for automatic segmentation of nuclei and/or cells for quantifications in other channels including foci detection

Wrapper code for segmentation of cells and nuclei with Cellpose.

This repository provides deep learning models trained on a large dataset of Pancreatic Ductal Adenocarcinoma Organoids co-cultured with immune cells.

Single-cell CFTR image-analysis pipeline for the mCherry-YFPCFTR quenching assay. The pipeline includes a custom-made Cellpose model for image segmentation, and per-cell quantification of CFTR membrane proximity and function.

End-to-end pipeline for spinal-cord microscopy segmentation with Cellpose, tiling, and mask stitching.

Открытый репозиторий с Jupyter-блокнотами для анализа микрореологических свойств эритроцитов с помощью машинного обучения, включая сегментацию и оценку деформируемости клеток

Python pipeline engine for scientific image analysis recipes, built for real-time adaptive feedback microscopy