Online Microscopy Resources

OpenPNM is an open-source pore network modelling package providing for a wide variety of pore-scale simulation tasks. It is designed to be fully agnostic to the topology and dimensionality of network by using graph theory representations to describe the architecture.

MorphoLibJ is a collection of mathematical morphology methods and plugins for ImageJ (morphological filtering/reconstruction, watershed segmentation, 2D/3D measurements, binary/label images utilities).

Successor of SR-Tesseler and Coloc-Tesseler, Point Cloud Analyst is an interactive software platform that allows the quantification of multi-dimensional and multi-colour point clouds data, with a focus on single-molecule localisation microscopy data.

Coloc-Tesseler is an interactive software platform that allows co-localisation analysis of 2D and 3D localisation microscopy data.

Prismatic is a CUDA/C++/Python GPU+CPU software package for fast image simulation in high resolution and scanning transmission electron microscopy (HRTEM & STEM) that includes a graphic user interface.

AFT is an open-source workflow to quantify alignment of fibrillar features in bioimages. It allows for evaluation of alignment lengthscale and works with a number of different imaging modalities.

py4DSTEM is a Python toolkit for analysis and visualisation of 4D-STEM data.

TomoPy is an open-source Python package for tomographic data processing and image reconstruction.

abTEM is a pure Python code for running simulations of (scanning) transmission electron microscopy images using the multi -slice or PRISM algorithms. It is open-source, blazing fast, and extremely versatile and easy to extend.

IPyvolume is a Python library to visualise 3D volumes and glyphs (e.g., 3D scatter plots), in Jupyter notebooks with minimal configuration and effort.

HyperSpy is an open-source Python library that provides tools to facilitate the interactive data analysis of multi-dimensional datasets that can be described as multi-dimensional arrays of a given signal.

DECODE is a Python and Pytorch based deep learning tool for high density 3D single molecule localisation microscopy (SMLM) analysis.

Gwyddion is a modular program for SPM (scanning probe microscopy) data visualisation and analysis. Primarily it is intended for the analysis of height fields obtained by scanning probe microscopy techniques (AFM, MFM, STM, SNOM/NSOM) and it supports a lot of SPM data formats.

SR-Tesseler is an open-source interactive single molecule localisation microscopy clustering tool based on Voronoï tesselation, that allows for segmentation and quantification of localisation-based super-resolution microscopy data.

PlantSeg is a tool for cell instance aware segmentation in densely packed 3D volumetric images. The pipeline is tuned for images acquired with confocal and light sheet microscopy and can be used to segment both plant and animal tissues.

StatSTEM provides a user-friendly way of quantifying atomic-resolution scanning transmission electron microscopy (STEM) images by using parametric model-based fitting. In this manner, accurate and precise quantitative information can be extracted about the material under investigation.

MULTEM is a collection of routines written in C++ with CUDA to perform accurate and fast multi-slice simulations for different transmission electron microscopy experiments (such as HRTEM, STEM, ISTEM, ED, PED, CBED, ADF-TEM, ABF-HC, EFTEM and EELS).

StarDist is an AI-based tool for object detection with star-convex shapes in 2D and 3D. Intended for cell nuclei detection/segmentation in microscopy images, it can be used via the stand-alone Python software package, or with the provided plugins for other common image analysis software suites (e.g., Fiji, napari, QuPath).

MicrobeJ is an analysis platform specifically built for automated analysis of the most common intensity, morphological and spatiotemporal measurements from bacterial datasets. MicrobeJ enables customised detection of unique features, is optimised for high-throughput, and has a rich user interaction.

Collection of Fiji macros to automate the boring stuff: batch process all files in a folder and save them by converting from .czi images (Bioformats) to .tif format; save all open images in .tif format in an output folder of choice; batch process all .tif files in a folder and save 3 channels separately; apply local contrast enhancement (CLAHE) to a Z-stack; batch segmentation of cell nuclei (or other blob-like objects) in fluorescence images by auto-thresholding.