celltracker.website

What It Is

CellTracker is image-processing software for cell migration assays, with a focus on cell detection, tracking, trajectory editing, and motion statistics in time-lapse microscopy images. It specifically emphasizes support for phase-contrast and DIC images, while also being able to process fluorescence images. The software is written in MATLAB and provides a graphical interface; users launch it by running CellTrackerGUI from the MATLAB command line.

Core Features and Tech Stack

Functionally, CellTracker covers the full analysis workflow: loading TIFF, AVI, and BioFormats files; cropping along the x-y or time dimensions; performing vignetting correction and automatic alignment; and then running automatic, semi-automatic, or manual tracking. Automatic tracking is based on template matching, with configurable detection thresholds, maximum displacement, minimum track length, and the number of frames to remember lost cells. Semi-automatic mode lets users select target cells first, while manual mode supports linear and dynamic interpolation. At the trajectory level, users can delete, merge, move, and modify IDs, as well as save or load .mat coordinate files.

Pricing, Deployment, and Ecosystem

The crawled text does not specify pricing, licensing, or whether the project is open source. Deployment is more like a local desktop tool: download a zip file, extract it, and run it in a MATLAB environment. It depends on MATLAB and Image Processing Toolbox 8.1, while some vignetting-correction features require Curve Fitting Toolbox 3.3 or later. This means the real cost of use may depend on MATLAB licensing. In terms of ecosystem integration, it can export XLS, CSV, and MAT files for further processing in Excel, MATLAB, or other analysis tools. It can also generate AVI videos and x-y-time 3D trajectory plots. Mac users should note that XLS export is not supported and must use CSV/MAT instead.

Pros, Cons, and Best-Fit Users

Its strengths are the comprehensive feature set for cell migration experiments, especially the detailed design around preprocessing, tracking, and trajectory correction for phase-contrast and DIC images. The documentation also provides substantial parameter explanations and operating instructions. The downsides are that the technology stack appears dated—the text mentions MATLAB 2009/2012—and the maintenance status is unclear. It also lacks information on APIs, SDKs, licensing, pricing, and support channels, making it unsuitable as a programmable component in a modern software engineering pipeline. It is better suited to life science researchers, microscopy imaging labs, and research workflows that require interactive correction of cell trajectories and exportable statistical results.

Access from China and Alternatives

Accessibility of the website from mainland China cannot be determined from the text alone, so it should be considered unknown. No payment information is provided either. If access or MATLAB licensing becomes a barrier, alternatives in the ImageJ/Fiji ecosystem, such as TrackMate and CellProfiler, are worth evaluating.