To achieve faster and more accurate segmentation results, we introduced a deep-learning segmentation algorithm. Segmentation of sperm images using U-Net++ Then, the rotational angular speed was calculated from the phase difference between consecutive frames. For the extracted image area, we used image segmentation to perform contour detection to obtain the projection phase of the head shape. Prior to the experiment, we calibrated the position of the optical trap and used a 150 \(\times\) 150 pixel region around the trap center as the region of interest (ROI) to exclude interference from other swimming sperms, as shown in Fig. The illumination of the sample chamber was provided by a LED light source and the imaging of the sample was performed using a CMOS camera (Sentech STC-mbs241U3V 163 fps). The sample solution of interest was loaded onto a sample pool and positioned at the back focal plane of the oil mirror, which was controlled using a voltage-controlled stage (Thorlabs ZFM2030). The beam is modulated through a reflective and pure phase-only liquid crystal spatial light modulator (Holoeye, HED6010-L-VIS) in the shaping system. The resulting linear polarized laser beam was then directed onto a dichroic mirror, which reflected it onto the back aperture of an oil immersion microscope objective (Nikon, 100 \(\times\) oil immersion NA = 1.4 WD = 0.13 mm). This laser beam was directed into a beam shaping system (BSS) for beam expansion. In our experimental setup, we employed a continuous wave laser (Coherent Verdi G, 2W) to generate a 532-nm laser beam. To obtain the projection phase information of the sperm, we used a self-designed optical tweezers system as shown in Fig. Our experiments analyzed the difference in rotational angular speed of sperm cells at different laser output power and verified that our method has potential applications in clinical research for sperm motility quantification and single sperm motility detection. This method is also suitable with other ellipsoidal-like cells or bacteria like Escherichia coli. We combine it with optical tweezers to dynamically trap sperms and analyze the rotational motility of individual sperm directly and simultaneously. In this study, we propose highly efficient method that extracting the orientation of the sperm head using deep learning-based segmentation. And compared with traditional methods, it has superior segmentation performance and robustness 16, 17.This tool can also be combined with optical tweezers and applied to axial localization of microspheres 18, optical force prediction of the optical tweezers 19, and trap stiffness measurement 20. Besides, for more complex motion patterns of sperm, such as rotation, the additional optical set-up should be designed, and corresponding algorithms to determine the three-dimensional motion of the sperm usually perform relatively slowly 12.ĭeep learning has been widely applied in the field of medical cell image segmentation, especially for particular cell counting 13, liver and liver-tumor segmentation 14, brain and brain-tumor segmentation 15 etc. However, In the high numerical aperture objective lens field of view, traditional segmentation methods have poor segmentation results due to complex background noise. employed this method to calculate the curvilinear velocity(VCL) of the head to characterize sperm activity 11. Currently, the main method for quickly tracking the movement of the head of a sperm cell involves tracking its centroid, which uses traditional clustering algorithms to segment 9, 10. This research direction has potential value in the single-sperm quality examination, which is crucial to the assistant reproductive technologies like intracytoplasmic sperm injection (ICSI) 8. Extensive research has been conducted on the dynamics of sperm cells trapped in optical tweezers, encompassing studies investigating diverse aspects such as chirality and motility force 6, 7. In this process, sperm with low motility will be screened out by barriers such as cervical mucus 5. During the reproductive process, sperms need to meet the egg through the female reproductive tract. Optical tweezers (OT) have been widely researched for trapping and manipulating micro-particles and microorganisms such as polystyrene beads, yeast cell, sperm and Escherichia coli 1, 2, 3, 4.
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