Human spermatozoa are the archetype of long-term self-organizing transport in nature and are critical for reproductive success. They utilize coordinated head and flagellar movements to swim long distances within the female reproductive tract in order to find and fertilize the egg. However, to date, long-term analysis of the sperm head–flagellar movements, or indeed those of other flagellated microorganisms, remains elusive due to limitations in microscopy and flagellar-tracking techniques. Here, we present a novel methodology based on local orientation and isotropy of bio-images to obtain long-term kinematic and physiological parameters of individual free-swimming spermatozoa without requiring image segmentation (thresholding). This computer-assisted segmentation-free method evaluates, for the first time, characteristics of the head movement and flagellar beating for up to 9.2 min. We demonstrate its powerful use by showing how releasing Ca²⁺ from internal stores significantly alters long-term sperm behavior. The method allows for straightforward generalization to other bio-imaging applications, such as studies of bull sperm and Trypanosoma, or indeed of other flagellated microorganisms – appealing to communities other than those investigating sperm biology.

人类精子是自然界中长期自组织运输的原型，对生殖成功至关重要。他们利用头部和鞭毛的协调运动在雌性生殖道中长距离游泳，以寻找并受精。然而，由于显微镜和鞭毛追踪技术的局限性，迄今为止，对精子头鞭毛运动或其他鞭毛微生物的长期分析仍然难以捉摸。在这里，我们提出了一种新的方法，基于生物图像的局部方向和各向同性，无需图像分割（阈值）即可获得个体自由游动精子的长期运动学和生理学参数。这种计算机辅助的无分段方法首次评估了 头部运动和鞭毛跳动的特征长达9.2分钟。我们通过展示如何释放钙来证明其强大的用途内部存储中的²⁺会大大改变长期的精子行为。该方法可以直接推广到其他生物成像应用，例如对公牛精子和锥虫的研究，或者对其他鞭毛微生物的研究，从而吸引了除研究精子生物学之外的其他社区。