[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Log in

Multiple sperm tracking in microscopic videos using modified GM-PHD filter

  • Original Paper
  • Published:
Machine Vision and Applications Aims and scope Submit manuscript

A Correction to this article was published on 30 January 2018

This article has been updated

Abstract

This paper presents a method for simultaneous tracking of multiple sperms using modified Gaussian mixture probability hypothesis density (GM-PHD) filter. In order to track sperms with spurious motion, a modified model is presented to adapt the GM-PHD filter for nonlinear dynamic movement of sperms. Furthermore, the “pruning” step in the GM-PHD filter is modified to handle situations like occlusion or closely moving targets. Our experiments demonstrate more effectivity of the proposed method in terms of sperms’ occlusion handling and trajectory extraction compared to the conventional GM-PHD filter. In particular, the new method performs well in managing the labels of occluded sperms after separation and in tracking of temporarily disappeared sperms when they emerge again in the tracking space.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

Change history

  • 30 January 2018

    In the original article, one of the co-author’s (Hamed Danandeh Hesar) first name has been published incorrectly. The correct given name should be Hamed.

Notes

  1. Multiple Hypothesis Tracking.

References

  1. Guzick, D.S., Overstreet, J.W., Factor-Litvak, P., Brazil, C.K., Nakajima, S.T., Coutifaris, C., et al.: Sperm morphology, motility, and concentration in fertile and infertile men. N. Engl. J. Med. 345, 1388–1393 (2001)

    Article  Google Scholar 

  2. Organization, W.H.: WHO Laboratory Manual for the Examination of Human Semen and Sperm-cervical Mucus Interaction, vol. 4. Cambridge University Press, Cambridge (1992)

    Google Scholar 

  3. Hirano, Y., Shibahara, H., Obara, H., Suzuki, T., Takamizawa, S., Yamaguchi, C., et al.: ANDROLOGY: relationships between sperm motility characteristics assessed by the computer-aided sperm analysis (CASA) and fertilization rates in vitro. J. Assist. Reprod. Genet. 18, 215–220 (2001)

    Article  Google Scholar 

  4. Sharon, M., David, M., Lynn, F.: Guidelines on the application of CASA technology in the analysis of spermatozoa. ESHRE andrology special interest group. European Society for Human reproduction and embryology. Hum. Reprod. 13, 142–145 (1998)

    Article  Google Scholar 

  5. Tomlinson, M.J., Pooley, K., Simpson, T., Newton, T., Hopkisson, J., Jayaprakasan, K., et al.: Validation of a novel computer-assisted sperm analysis (CASA) system using multitarget-tracking algorithms. Fertil. Steril. 93, 1911–1920 (2010)

    Article  Google Scholar 

  6. Sørensen, L., Østergaard, J., Johansen, P., de Bruijne, M.: Multi-object tracking of human spermatozoa. In: Proceedings SPIE, Medical Imaging: Image Processing, 2008, vol. 6914, p. 69142C (2008)

  7. Pascual-Gaspar, J., Olmedo, H., Exposito, A., Exposito, A., Finat, J.: A simple and effective system for computer-assisted semen analysis. In: 4th IET International Conference on Advances in Medical, Signal and Information Processing - MEDSIP 2008, Santa Margherita Ligure, 2008, pp. 1–4 (2008)

  8. Shi, L.Z., Nascimento, J.M., Chandsawangbhuwana, C., Botvinick, E.L., Berns, M.W.: An automatic system to study sperm motility and energetics. Biomed. Microdevices 10, 573–583 (2008)

    Article  Google Scholar 

  9. Nafisi, V.R., Moradi, M.H., Nasr-Esfahani, M.H.: A template matching algorithm for sperm tracking and classification. Physiol. Meas. 26, 639 (2005)

    Article  Google Scholar 

  10. Mahler, R.P.: Multitarget Bayes filtering via first-order multitarget moments. IEEE Trans. Aerosp. Electron. Syst. 39, 1152–1178 (2003)

    Article  Google Scholar 

  11. Vo, B.-N., Ma, W.-K.: The Gaussian mixture probability hypothesis density filter. IEEE Trans. Signal Process. 54, 4091–4104 (2006)

    Article  MATH  Google Scholar 

  12. Clark, D., Vo, B.-T., Vo, B.-N.: Gaussian particle implementations of probability hypothesis density filters. In: Aerospace Conference. IEEE 2007, pp. 1–11 (2007)

  13. Panta, K., Clark, D.E., Vo, B.-N.: Data association and track management for the Gaussian mixture probability hypothesis density filter. IEEE Trans. Aerosp. Electron. Syst. 45, 1003–1016 (2009)

    Article  Google Scholar 

  14. Eiselein, V., Arp, D., Pätzold, M., Sikora, T.: Real-time multi-human tracking using a probability hypothesis density filter and multiple detectors. In: 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance (AVSS), pp. 325–330 (2012)

  15. Yazdian-Dehkordi, M., Azimifar, Z., Masnadi-Shirazi, M.: Competitive Gaussian mixture probability hypothesis density filter for multiple target tracking in the presence of ambiguity and occlusion. IET Radar Sonar Navig. 6, 251–262 (2012)

  16. Eiselein, V., Senst, T., Keller, I., Sikora, T.: A motion-enhanced hybrid probability hypothesis density filter for real-time multi-human tracking in video surveillance scenarios. In: 2013 IEEE International Workshop on Performance Evaluation of Tracking and Surveillance (PETS), pp. 6–13 (2013)

  17. Si, W., Wang, L., Qu, Z.: Multi-target tracking using an improved Gaussian mixture CPHD filter. Sensors 16, 1964 (2016)

    Article  Google Scholar 

  18. Reid, D.: An algorithm for tracking multiple targets. IEEE Trans. Autom. Control 24, 843–854 (1979)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hamid Abrishami Moghaddam.

Additional information

The original version of this article was revised: one of the co-author’s (Hamed Danandeh Hesar) first name has been published incorrectly.

A correction to this article is available online at https://doi.org/10.1007/s00138-018-0910-6.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hesar, H.D., Abrishami Moghaddam, H., Safari, A. et al. Multiple sperm tracking in microscopic videos using modified GM-PHD filter. Machine Vision and Applications 29, 433–451 (2018). https://doi.org/10.1007/s00138-017-0897-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00138-017-0897-4

Keywords

Navigation