Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups.
Consists of a tracking Matlab software. u-track is a program designed to perform several actions: (1) track dense particle fields, (2) close gaps in particle trajectories resulting from detection failure, and (3) capture particle merging and splitting events resulting from occlusion or genuine aggregation and dissociation events. Its core is based on formulating correspondence problems as linear assignment problems and searching for a globally optimal solution.
Analyzes, processes and visualizes multi-dimensional microscopy images. BioImageXD puts open-source computer science tools for three-dimensional visualization and analysis into the hands of all researchers, through a user-friendly graphical interface tuned to the needs of biologists. BioImageXD has no restrictive licenses or undisclosed algorithms and enables publication of precise, reproducible and modifiable workflows. It allows simple construction of processing pipelines and should enable biologists to perform challenging analyses of complex processes.
Assists in analysing cell shape and motion. 3D cell shape and migration allows users to study the correlation between these shape and motion parameters and subcellular fluorescence localization. It is based on a 3D Gaussian partial-derivative kernel surface filtering algorithm. This method is combined with a self-adjusting high intensity threshold.
A free, open-source system designed for flexible, high-throughput cell image analysis. CellProfiler can address a variety of biological questions quantitatively, including standard assays (for example, cell count, size, per-cell protein levels) and complex morphological assays (for example, cell/organelle shape or subcellular patterns of DNA or protein staining).
Correlates local cortical fluorescence with membrane movement. Quimp is based on the electrostatic contour migration method (ECMM) that consists of an improvement of a boundary tracking approach. It reduces sum of path lengths connecting all pairs of points, equivalent to minimizing the energy required for cell deformation. This tool is useful to study time series of several hundreds of cells per experimental condition.
Supplies a simultaneous analysis of size and composition of nanoparticles, on a single particle basis. SPARTA provides a package leaning on a high-end confocal Raman spectroscopy set-up. This program enables high throughput, routine analysis of individual nanoparticles in solution without requiring particle labelling or modification. It can also be used for resolving mixtures and investigating particle heterogeneity.
Allows quantification of clathrin-coated pit dynamics from fluorescence time-lapse data. cmeAnalysis provides functionalities including: (1) sensitive detection, (2) tracking (based on u-track), (3) master/slave detection for multi-channel data, (4) intensity-based classification of coated structures, and (5) lifetime analysis. It also contains a graphical user interface (GUI) for inspection of analysis results from individual movies.
An easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. KiT includes a user-friendly GUI (Graphical User Interface) for selecting ROIs (Regions Of Interest; to select cells and exclude spurious background fluorescence), parameter configuration and execution of KiT. Tracking may be executed from within the GUI or later. The GUI allows selection of particle detection algorithms per channel and modification of the most commonly used options. KiT also includes a GUI for post-tracking processing, enabling basic diagnostics and track quantification, such as kinetochore speeds and autocorrelation. The GUI collates data from each tracked ROI and saves a .mat file for later user-specific processing.
The performance of the single particle tracking (SPT) nearest-neighbor algorithm is determined by parameters that need to be set according to the characteristics of the time series under study. Inhomogeneous systems, where these characteristics fluctuate spatially, are poorly tracked when parameters are set globally. adaptiveSPT is a SPT approach that adapts the well-known nearest-neighbor tracking algorithm to the local density of particles to overcome the problems of inhomogeneity.
Allows users to locate and track single molecules. TrackNTrace intends to provide a centralized platform to: (i) identify single particles or patterns, (ii) refine their positions and extract parameters and lastly (iii) perform their tracking. This software is based on modular system, developed with the aim of easing the incorporation of external algorithms according users' needs. Besides, it can also be applied to microtubule-tip tracking or imaging with engineered point spread functions (PSFs).
A 2D and 3D feature point-tracking tool for the automated detection and tracking of particle trajectories as recorded by video imaging in cell biology. Particle Tracker is part of the MOSAICsuite, which also offers image segmentation, interaction analysis, and much more.
A Matlab software package for tracking the full dynamics of microtubules based on +TIP marker live cell image sequences. Concepts are related to the ClusterTrack software; however, the tracking builds on the algorithms implemented in the u-track software. The package can be operated via a convenient graphical user interface. It contains a sizable set of service functions for data visualization and statistical processing of parameters of microtubule dynamics.
Supports local analysis and is able to split a single trajectory into segments with different motion types. TraJClassifier is a Fiji plugin providing a practical and device-independent method to classify and segment particle trajectories into four main motion types. It loads trajectories from TrackMate (exported via the action "Export trajectories"), characterizes them using TraJ and classifies them into normal diffusion, subdiffusion, confined diffusion and directed/active motion by a random forest approach (through Renjin).
Simulates lifelike trajectories for some particles. MOPSA is a microfluidics-optimized particle simulation algorithm that can treat particle as a 2D rigid circular object instead of a single point when calculating the particle’s velocity. This tool also checks whether the particle overlaps a solid object at each simulated time step.
Allows spatial point pattern and interaction analysis. MosaicIA provides standardized ways to (1) correct for the influence of the distribution of points within one set onto the distance distribution to another set; (2) infer parameters of the interaction potential, such as the strength and length scale of the interaction; (3) perform statistical hypothesis tests for the presence of an interaction. It has been tested on both synthetic and real-world data.
A free and open-source tool that complements the object tracking functionality of the CellProfiler biological image analysis package. CellProfiler Tracer allows multi-parametric morphological data to be visualized on object tracks, providing visualizations that have already been validated within the scientific community for time-lapse experiments, and combining them with simple graph-based measures for highlighting possible tracking artifacts.
A 4-D image processing platform for the work with laser scanning and wide field microscopes. TIKAL provides a registration software for correcting global movements and local deformations of cells as well as 2-D and 3-D tracking software.
A robust and fast computational procedure for tracking fluorescent markers in time-lapse microscopy. The algorithm is optimized for finding the time-trajectory of single particles in very noisy image sequences. The optimal trajectory of the particle is extracted by applying a dynamic programming optimization procedure. In addition, SpotTracker includes an optimal filter to enhance a Gaussian-like spot while attenuating the background noise.
Aims to analyze the dynamics of macromolecular assemblies with high spatial and temporal resolution. QFSM allows users to study spatial and temporal relations between the formation, turnover, and mechanical outputs of the filament network. It assists in identifying and tracking speckles and utilizes their location, appearance, and disappearance to derive network flows and assembly/disassembly maps.