The dataset repository consists of 2D and 3D time-lapse sequences of fluorescently counterstained nuclei or cells moving on top or immersed in a substrate, along with 2D brightfield, phase contrast, and differential interference contrast microscopy videos of cells moving on a flat substrate. In addition, we provide 2D and 3D videos of computer-generated fluorescent cells and nuclei of different shapes and motion patterns.
All 2D+t and 3D+t datasets are available for download to anyone. Please check carefully the “Conditions of use of the images” section at the end of this page before downloading any of these datasets. For technical support, please contact Martin Maška (firstname.lastname@example.org).
Both the original image data and all available reference annotations can be downloaded as a single ZIP archive for each training dataset. The test datasets are distributed as the ZIP archives too, but without reference annotations. Individual files in the ZIP archives were named and created following the conventions described in:
Conditions of use of the images:
1) Please include a reference to this Nature Methods paper and optionally to its predecessor, and acknowledge the data source (the Cell Tracking Challenge) in any publication resulting from the use of any of our datasets.
2) Any CTC-related use of our datasets, i.e. any use aimed at preparing your submission, participating in the challenge, or reporting the results, does not require explicit consent from the challenge organizers or the data providers.
3) Any public non-CTC-related, scientific use of our datasets requires explicit permission from the challenge organizers.
4) Any commercial use of our datasets requires explicit permission from the challenge organizers and the data providers listed in the description of the datasets.
5) Cloning of our datasets or their parts, including reference annotations, is strictly forbidden. If you must provide evidence or support of the existence of our datasets, please do it using the download links included in the description of the datasets.