Cell segmentation

Histology Topography Cytometry Analysis Toolbox (histoCAT) is a package to visualize and analyse multiplexed image cytometry data interactively. It can also export data in.fcs data for further analysis using  a specialized cytometry sofwtare such as Flowjo. 

It can be run as a compiled standalone or from matlab.

BioImage.IO -- a collaborative effort to bring AI models to the bioimaging community. 

• Integrated with Fiji, ilastik, ImJoy and more
• Try model instantly with BioEngine
• Contribute your models via Github

This is a database of pretrained deep Learning models. 

LOBSTER (Little Objects Segmentation and Tracking Environment), an environment designed to help scientists design and customize image analysis workflows to accurately characterize biological objects from a broad range of fluorescence microscopy images, including large images, i.e. terabytes of data, exceeding workstation main memory.

• 75 workflows available 
• no programming, with GUI
• matlab based 

This is the ImageJ/Fiji plugin for StarDist, a cell/nuclei detection method for microscopy images with star-convex shape priors ( typically for Dapi like staining of nuclei). The plugin can be used to apply already trained models to new images.

Summary

Deep learning-based segmentation of cells, both fluorescence, and bright-field images ("a generalist algorithm for cellular segmentation"). The tool can be used either online or local or via notebooks (e.g. ZeroCostDL4Mic).

How to use it

cellpose can be used online via ready-to-use Jyupyter notebooks with very good documentation. These notebooks are listed here.

Local Installation

The general local installation procedure can be found here.

... Installing to Silicon Mac (M1 processor) needs some tricks, and as of October 2021, the following sequence of commands works. numba should be conda-installed before pip-installing the cellpose.

conda create --name cellpose python=3.8
conda activate cellpose
conda install numba
git clone https://github.com/MouseLand/cellpose.git
cd cellpose
pip install -e .