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A simple toolbox of two ImageJ plugins for quantifying adipocyte morphology and function in tissues and in vitro.

Analysis of conditional colocalization relationships and hierarchies from three-color microscopy images.

A cross-platform GUI software for automatically generating and analyzing kymographs of membrane-cortex associated proteins or lipids from live-cell time-lapse fluorescent imaging datasets. It automates complex boundary tracking and spatiotemporal analysis of cell mechanics.

Deep Learning Enabled Accurate Segmentation of Budding Yeast Cells in Bright-field Microscopy. YeastNet: Deep Learning Semantic Segmentation for Budding Yeast Single Cell Analysis. YeastNet is a library for analysing live-cell fluorescence microscopy of budding yeast cells, written in Python3 using PyTorch 1.0.

An ImageJ/FIJI macro to identify, count, and measure synaptic puncta from fluorescent images.

A tool for Traction Force and Monolayer Stress Microscopy. pyTFM is a python package that allows you to analyze force generation and stresses in cells, cell colonies and confluent cell layers growing on a 2 dimensional surface. This package implements the procedures of Traction Force Microscopy and Monolayer Stress Microscopy. In addition to the standard measures for stress and force generation, it also includes the line tension, a measure for the force transfer exclusively across cell-cell boundaries. pyTFM includes an addon for the image annotation tool clickpoints allowing you to quickly analyze and vizualize large datasets.

Analyzing engineered point spread functions using phasor-based single-molecule localization microscopy.

MotilA is a Python pipeline for quantifying microglial fine process motility from 3D time-lapse microscopy data. It performs image preprocessing, segmentation, and motility quantification, yielding biologically interpretable metrics and is suitable for various imaging applications.

Python-based bespoke microscopy for bio-medical science. Cockpit is a microscope graphical user interface. It is a flexible and easy to extend platform aimed at life scientists using bespoke microscopes. More detailed information is available:. Micron Advanced Imaging Consortium. Micron Advanced Imaging ConsortiumMicron Advanced Imaging ConsortiumMicron Advanced Imaging Consortium.

DeepMM is a too for automatic de novo atomic-accuracy structure determination for cryo-EM maps using deep learning.

CaPTure allows for rapid assessment of neuronal activity in cultured cells at cellular resolution, rendering it amenable to high-throughput screening and phenotypic discovery. The platform can be applied to both human- and rodent-derived neurons and is compatible with many imaging systems.

Inferring Chromosome Radial Organization from Hi-C Data. The included Python scripts (mat2net.py, and predictCTpos.py) contain an implemention of the HIRAC computational technique described in the following manuscript.

Microscope is a Python package for the control of automated microscopes. It is easy to use and especially well suited for complex microscopes with hard timing requirements. It is aimed at those that are building their own microscopes or want programmatic control for microscope experiments.

PyHIST is a Histological Image Segmentation Tool: a lightweight semi-automatic pipeline to extract tiles with foreground content from SVS histopathology whole image slides (with experimental support for other formats). It is intended to be an easy-to-use tool to preprocess histological image data for usage in machine learning tasks. The PyHIST pipeline involves three main steps: 1) produce a mask for the input WSI that differentiates the tissue from the background, 2) create a grid of tiles on top of the mask, evaluate each tile to see if it meets the minimum content threshold to be considered as foreground and 3) extract the selected tiles from the input WSI at the requested resolution.

2D segmentation and 3D reconstruction for fission yeast and other radially symmetric cells. Pomegranate is a nuclear and whole-cell detection, reconstruction, and 3D segmentation tool for static images of fission yeast. See the Documentation folder for all user guides, tutorials and documentation. Included here are a quick start guide to get Pomegranate installed via the Hauf Lab update site, as well as the accompanying Pomegranate User Guide. The Pomegranate User Guide will contain a link to a repository containing samples images and outputs.

An Open Source Standalone Deep Learning Application for Microscopic Image Analysis.

EZcalcium is a flexible, user-friendly toolbox for analysis of calcium imaging data, controlled by a set of intuitive graphical user interfaces (GUI) based on MATLAB.