Deep learning-based method for analyzing the optically trapped sperm rotation.
Journal:
Scientific reports
PMID:
37537346
Abstract
Optical tweezers exert a strong trapping force on cells, making it crucial to analyze the movement of trapped cells. The rotation of cells plays a significant role in their swimming patterns, such as in sperm cells. We proposed a fast deep-learning-based method that can automatically determine the projection orientation of ellipsoidal-like cells without additional optical design. This method was utilized for analyzing the planar rotation of trapped sperm cells using an optical tweezer, demonstrating its feasibility in extracting the rotation of the cell head. Furthermore, we employed this method to investigate sperm cell activity by examining variations in sperm rotation rates under different conditions, including temperature and laser output power. Our findings provide evidence for the effectiveness of this method and the rotation analysis method developed may have clinical potential for sperm quality evaluation.