Description
Accurate cell tracking is essential to various biological studies. In this talk, we present Ultrack, a novel Python package for cell tracking that considers a set of multiple segmentation hypotheses and picks the segments that are most consistent over time, making it less susceptible to mistakes when traditional segmentation fails. The package supports various imaging modalities, from small 2D videos to terabyte-scale 3D time-lapses or multicolored datasets in any napari-compatible image format (e.g. tif, zarr, czi, etc.). It is available at https://github.com/royerlab/ultrack