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.
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).
Superresolution Microscopy Analysis Platform (SMAP) is a freely available all-in-one analysis package for 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.
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.
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.
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.
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.
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.
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).
