4 research outputs found
The Cell Tracking Challenge: 10 years of objective benchmarking
The Cell Tracking Challenge is an ongoing benchmarking initiative that
has become a reference in cell segmentation and tracking algorithm
development. Here, we present a signifcant number of improvements
introduced in the challenge since our 2017 report. These include the
creation of a new segmentation-only benchmark, the enrichment of
the dataset repository with new datasets that increase its diversity and
complexity, and the creation of a silver standard reference corpus based
on the most competitive results, which will be of particular interest for
data-hungry deep learning-based strategies. Furthermore, we present
the up-to-date cell segmentation and tracking leaderboards, an in-depth
analysis of the relationship between the performance of the state-of-the-art
methods and the properties of the datasets and annotations, and two
novel, insightful studies about the generalizability and the reusability
of top-performing methods. These studies provide critical practical
conclusions for both developers and users of traditional and machine
learning-based cell segmentation and tracking algorithms.Web of Science2071020101