The study of human sperm motility has been a topic of interest for decades due to its crucial role in fertility and reproductive health. While most analyses rely on 2D+t imaging of head trajectories, sperm naturally swim in three dimensions (3D), driven by complex flagellar motion. However, the lack of comprehensive 3D+t datasets has limited progress in this field. To address this, we present 3D-SpermFlagella, the first large-scale 3D+t dataset of human sperm flagellum centerline annotations. This dataset contains 135 tracked and annotated sperm, derived from our previously published multifocal video microscopy dataset 3D-SpermVid. Each flagellar centerline was annotated over time in three dimensions, incubated under non-capacitating (NCC) and capacitating (CC) conditions. The (x,y,z) coordinates are provided in both micrometers and voxels, making 3D-SpermFlagella a valuable resource for studying sperm motility in its full spatial complexity and for the development and benchmarking of AI-based models for tracking and segmentation. In this paper, we describe the segmentation and tracking methods, as well as the conditions and structure of the dataset.
Hernandez-Herrera et al. (2026) studied this question.