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A hybrid IMM-JPDAF algorithm for tracking multiple sperm targets and motility analysis

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Abstract

Semen analysis has received a lot of attention because of its important role in determining infertility in men. It involves several factors, the most important of which are sperm morphology, sperm concentration, and sperm motility. In addition, measurements of sperm cell mobility reflect important parameters in medical diagnosis. As computer-assisted semen analysis systems are very expensive and not prolific, especially in small medical laboratories, semen analysis is often done manually. This is a time-consuming and costly process. Therefore, we have developed an automated system that evaluates sperm motility parameters which can be of great help to clinicians in achieving more accurate results at a lower cost and time. The system tracks the movement of most spermatozoa cells in a semen sample taken from a microscope and then carefully measures all the parameters related to sperm movement to determine the fertility or infertility rate of the subject. Detecting large numbers of sperm cells is challenging because there are a large number of colliding targets that cause false alarms. In this work, the background subtraction method is used to determine the sperms within the video frames, and the joint probabilistic data association filter algorithm is used to estimate the sperm trajectory and to associate different tracks. Since the sperm represents maneuvering movements, the interacting multiple models technique was used along with the JPDAF algorithms to obtain more accurate results. Our evaluations on real and synthetic data reveal the superiority of our method over previous work in sperm cell tracking.

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Acknowledgements

We would like to thank Turks Abroad and Related Communities (YTB) for economically supporting İnas Alarabi during her master thesis. We would like to thank also Assoc. Prof. Dr. Emrah Hicazi Aksu from the Department of Reproduction and Artificial Insemination and Prof. Dr. Abdulsamet Hasiloglu from the Computer Engineering Department, at Ataturk University for giving us insightful information about sperm behavior on videos.

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Author notes

  1. Gulsah Tumuklu Ozyer, Baris Ozyer and Farhood Negin have contributed equally to this work.

Authors and Affiliations

  1. Computer Engineering Department, Ataturk University, 25240, Erzurum, Turkey

    Gulsah Tumuklu Ozyer, Baris Ozyer & İnas Alarabi

  2. Inria, 06902, Valbonne, France

    Farhood Negin

  3. Computer Engineering Department, Erzurum Technical University, 25050, Erzurum, Turkey

    Saeid Agahian

Authors
  1. Gulsah Tumuklu Ozyer
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  2. Baris Ozyer
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  3. Farhood Negin
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  4. İnas Alarabi
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  5. Saeid Agahian
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Correspondence to Baris Ozyer.

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Tumuklu Ozyer, G., Ozyer, B., Negin, F. et al. A hybrid IMM-JPDAF algorithm for tracking multiple sperm targets and motility analysis. Neural Comput & Applic 34, 17407–17421 (2022). https://doi.org/10.1007/s00521-022-07390-3

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  • DOI: https://doi.org/10.1007/s00521-022-07390-3

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