Image Analysis Resources

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.

Atomap is a Python library for analysing atomic resolution scanning transmission electron microscopy images. It relies on fitting 2D Gaussian functions to every atomic column in an image, and automatically finds all major symmetry axes.

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.

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).

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.

ParticleSpy is a Python package that eases segmentation and analysis of nanoparticles from electron microscopy data. It is built on the HyperSpy package and can be used with any data loaded via HyperSpy.

PoreSpy is a collection of image analysis tools used to extract information from 3D images of porous materials.

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.

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

pyxem is an open-source Python library for multi-dimensional diffraction microscopy. It has been primarily developed as a platform for hybrid diffraction-microscopy based on 4D scanning diffraction microscopy data in which a 2D diffraction pattern is recorded at every position in a 2D scan of a specimen.

riCOM provides real-time image reconstruction methods for scanning transmission electron microscopy (STEM).

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.

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

TrackPy is a Python package for particle tracking in 2D, 3D and higher dimensions. It can be used at a range of length scales and applied to image stacks recorded using both light microscopy and electron microscopy.

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.

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

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

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

Microscopy Image Browser (MIB) is a package for image processing, segmentation, and visualisation of multi-dimensional (2D-4D) microscopy datasets.

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.

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

NanoJ is an open-source toolbox for super-resolution microscopy data analysis. It encompasses several essential processing steps; spatiotemporal alignment of raw data (NanoJ-Core), super-resolution image reconstruction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics).

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.

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.

This is an open-source suite to mathematically model turnover rates in an intervention-free manner given the ability to quantify mRNA and protein expression from initiation to homeostasis.

PyTorch-3dunet is an easy-to-use package for training neural networks to solve 2D and 3D segmentation problems

Superresolution Microscopy Analysis Platform (SMAP) is a freely available all-in-one analysis package for single molecule localisation microscopy data.

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.

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).

TRABI (temporal, radial-aperture-based intensity estimation) is a free ImageJ macro used for 3D processing of 2D single molecule microscopy data. Through intensity estimation in different regions of the emission pattern of single fluorophores, a relative 3D position can be determined from 2D data with no adaptation to the microscope.

ZeroCostDL4Mic is an open-source toolbox of deep learning-based tools for microscopy image processing and analysis.

Analysis code for AFM raw data post-processing and Hertz model calculation to obtain Young's modulus for increasing indentation depths.

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.