Evaluation of Multi-Target Human Sperm Tracking Algorithms in Synthesized Dataset

Infertility is an important issue for many couples and male infertility is highly related to semen and spermatozoa which can be surveyed by means of semen/sperm analysis. Many fertility assessment laboratories are now equipped with automatic systems called Computer Aided Semen/Sperm Analysis (CASA) for doing this task. Evaluation of such systems is very important. In this research a web-based simulator is developed which facilitates evaluation of CASA systems. The developed software has many useful parameters such as blurring images or adding noise and it also gives full control of sperm counts and types. To illustrate performance of the developed simulator, many parameters such as spermatozoa population, standard deviation of Gaussian blur filter and noise intensity have been swept and the results of two well-known multi-target tracking systems (Linear Kalman Filter and Particle Filter) were compared and discussed.