Abstract
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.
Data availability
The 3D-SpermFlagella2 dataset is openly accessible in the Zenodo repository at the following link: https://doi.org/10.5281/zenodo.15299846.
Code availability
The code utilized for the semi-automated workflow, responsible for tracing the sperm head and flagellum centerline, is openly accessible on https://github.com/paul-hernandez-herrera/LIVC_UNAM/tree/main/matlab_code/Sperm_tracing_3D_Release.
References
Montoya, F. et al. 3D+t Multifocal Imaging Dataset of Human Sperm. Sci Data 12, 814, https://doi.org/10.1038/s41597-025-05177-4 (2025).
Hernandez-Herrera, P. et al. 3D-SpermFlagella: 3D+t human sperm flagellum centerline dataset [Data set]. Zenodo https://doi.org/10.5281/zenodo.15299846 (2025).
Saggiorato, G. et al. Human sperm steer with second harmonics of the flagellar beat. Nature communications 8(1), 1415 (2017).
Nassir, M., Levi, M. & Shaked, N. T. Dynamic 3D Modeling for Human Sperm Motility through the Female Cervical Canal and Uterine Cavity to Predict Sperm Chance of Reaching the Oocyte. Cells 12(1), 203 (2023).
Powar, S. et al. Unraveling the kinematics of sperm motion by reconstructing the flagellar wave motion in 3d. Small Methods 6(3), 2101089 (2022).
Gong, A. et al. Reconstruction of the three-dimensional beat pattern underlying swimming behaviors of sperm. The European Physical Journal E 44(7), 87 (2021).
Gallagher, M. T., Kirkman-Brown, J. C. & Smith, D. J. Axonemal regulation by curvature explains sperm flagellar waveform modulation. PNAS nexus 2(3), pgad072 (2023).
Díaz-Guerrero, D. S. et al. Computation of Human-Sperm Local Flagellar Instantaneous Velocity. In Congreso Nacional de Ingeniería Biomédica (pp. 59-66). Cham: Springer Nature Switzerland (2023, October).
Bribiesca-Sánchez, A. et al. Artifacts generated by the 3D rotation of a freely-swimming human sperm in the measurement of intracellular Ca2+. In Congreso Nacional de Ingeniería Biomédica (pp. 355-362). Cham: Springer International Publishing (2022, October).
Alquézar-Baeta, C. et al. OpenCASA: A new open-source and scalable tool for sperm quality analysis. PLoS computational biology 15(1), e1006691 (2019).
Walker, B. J., Phuyal, S., Ishimoto, K., Tung, C. K. & Gaffney, E. A. Computer-assisted beat-pattern analysis and the flagellar waveforms of bovine spermatozoa. Royal Society open science 7(6), 200769 (2020).
Guasto, J. S. et al. Flagellar kinematics reveals the role of environment in shaping sperm motility. Journal of the Royal Society Interface 17(170), 20200525 (2020).
Tufoni, C. et al. Flagellar beating forces of human spermatozoa with different motility behaviors. Reproductive Biology and Endocrinology 22(1), 28 (2024).
Yazdan Parast, F. et al. Viscous loading regulates the flagellar energetics of human and bull sperm. Small Methods 8(7), 2300928 (2024).
Hackerova, L. et al. Boar Sperm Motility Assessment Using Computer-Assisted Sperm Analysis: Current Practices, Limitations, and Methodological Challenges. Animals 15(3), 305 (2025).
Ghasemian, F., Mirroshandel, S. A., Monji-Azad, S., Azarnia, M. & Zahiri, Z. An efficient method for automatic morphological abnormality detection from human sperm images. Computer methods and programs in biomedicine 122(3), 409–420 (2015).
Javadi, S. & Mirroshandel, S. A. A novel deep learning method for automatic assessment of human sperm images. Computers in biology and medicine 109, 182–194 (2019).
Shaker, F., Monadjemi, S. A., Alirezaie, J. & Naghsh-Nilchi, A. R. A dictionary learning approach for human sperm heads classification. Computers in biology and medicine 91, 181–190 (2017).
Ilhan, H. O., Sigirci, I. O., Serbes, G. & Aydin, N. A fully automated hybrid human sperm detection and classification system based on mobile-net and the performance comparison with conventional methods. Medical & biological engineering & computing 58, 1047–1068 (2020).
Thambawita, V. et al. VISEM-Tracking, a human spermatozoa tracking dataset. Scientific Data 10(1), 1–8 (2023).
Dardikman-Yoffe, G., Mirsky, S. K., Barnea, I. & Shaked, N. T. High-resolution 4-D acquisition of freely swimming human sperm cells without staining. Science advances 6(15), eaay7619 (2020).
Chang, V., Garcia, A., Hitschfeld, N. & Härtel, S. Gold-standard for computer-assisted morphological sperm analysis. Computers in biology and medicine 83, 143–150 (2017).
Corkidi, G., Taboada, B., Wood, C. D., Guerrero, A. & Darszon, A. Tracking sperm in three dimensions. Biochemical and biophysical research communications 373(1), 125–129 (2008).
Bribiesca-Sánchez, A. et al. A Three-Dimensional Extension of the Slope Chain Code: Analyzing the Tortuosity of the Flagellar Beat of Human Sperm (2023).
Hernández, H. O. et al. Feature-based 3D+ t descriptors of hyperactivated human sperm beat patterns. Heliyon, 10(5) (2024).
Hernández, H. O. et al. 3D+ t feature-based descriptor for unsupervised flagellar human sperm beat classification. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 488-492). IEEE (2022, July).
Guzmán, A., Darszon, A., Corkidi, G. & Bribiesca, E. A Measure of Tortuosity for 3D Curves: Identifying 3D Beating Patterns of Sperm. In Pattern Recognition and Image Analysis: 11th Iberian Conference, IbPRIA 2023, Alicante, Spain, June 27–30, 2023, Proceedings (Vol. 14062, p. 363). Springer Nature (2023, June).
The MathWorks Inc. MATLAB version: 24.1.0 (R2024a), Natick, Massachusetts: The MathWorks Inc. https://www.mathworks.com (2024).
Hernandez-Herrera, P., Montoya, F., Rendón-Mancha, J. M., Darszon, A. & Corkidi, G. 3-D +T Human Sperm Flagellum Tracing in Low SNR Fluorescence Images. IEEE transactions on medical imaging 37(10), 2236–2247 (2018).
Santamaría-Pang, A., Hernandez-Herrera, P., Papadakis, M., Saggau, P. & Kakadiaris, I. A. Automatic morphological reconstruction of neurons from multiphoton and confocal microscopy images using 3D tubular models. Neuroinformatics 13, 297–320 (2015).
Arshadi, C., Günther, U., Eddison, M., Harrington, K. I. & Ferreira, T. A. SNT: a unifying toolbox for quantification of neuronal anatomy. Nature methods 18(4), 374–377 (2021).
Hernández-Herrera, P. et al. Supplementary videos for 3D-SpermFlagella dataset. Zenodo https://doi.org/10.5281/zenodo.18434653 (2026).
van der Horst, G. Computer Aided Sperm Analysis (CASA) in domestic animals: Current status, three D tracking and flagellar analysis. Animal reproduction science 220, 106350 (2020).
Acknowledgements
This project has been made possible in part by a grant number 2023-329644 from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation. SECIHTI scholarship was granted to ABS. This work was supported in part by the Universidad Nacional Autónoma de México (UNAM) - Programa de Apoyo a Proyectos de Investigación e Innovación Tecnológica (PAPIIT) projects IT101624, IN108624 and IN227925.
Author information
Authors and Affiliations
Contributions
Conceptualization: P.H.-H., H.O.H., F.M., A.B.-S., D.S.D.-G., A.D., G.C.; Methodology: P.H.-H., H.O.H., F.M., A.B.-S., D.S.D.-G., A.D., G.C.; Software: P.H.-H., H.O.H., F.M., A.B.-S.; Validation: P.H.-H., H.O.H., F.M., A.B.-S., D.S.D.-G., G.C.; Resources: P.H.-H., A.D., G.C.; Writing - original draft: P.H.-H., H.O.H., A.B.-S.; Writing - review & editing: P.H.-H., H.O.H., A.B.-S., F.M., D.S.D.-G., A.D., G.C.; Project administration: P.H.-H., A.D., G.C.; Funding acquisition: P.H.-H., A.D., G.C.
Corresponding authors
Ethics declarations
Competing interests
The authors confirm that they have no financial interests or personal relationships that could have influenced the work presented in this paper.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Hernández-Herrera, P., Hernández, H.O., Bribiesca-Sanchez, A. et al. 3D+t human sperm flagellum centerline dataset. Sci Data (2026). https://doi.org/10.1038/s41597-026-06876-2
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41597-026-06876-2
