Abstract
Now a days, the infertility is a big problem for human being, especially for men. The mobility of the sperm does not depend on the number of sperm present in the semen. To avoid infertility, the detection rate of the multi moving sperms is to measured. There are different algorithms are utilized for detection of sperms in the human semen, but their detection rate is not up to the mark. This article proposed a method to track and detect the human sperm with high detection rate as compared to existing approaches. The sperm candidates are tracked using Kalman filters and proposed algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Speroff L, Fritz MA. Clinical gynecologic endocrinology and infertility: Lippincott Williams & Wilkins; 2004.
Wenzhong Y, Shuqun S. Automatic Chromosome Counting Algorithm Based on Mathematical Morphology. Journal of Data Acquisition & Processing. 2008;23(9):1004–9037.
Menkveld R, Wong WY, Lombard CJ, Wetzels AM, Thomas CM, Merkus HM, et al. Semen parameters, including WHO and strict criteria morphology, in a fertile and subfertile population: an effort towards.
Standardization of in-vivo thresholds. Hum Reprod. 2001 Jun;16(6):1165–71.
Leung C, Lu Z, Esfandiari N, Casper RF, Sun Y, editors. Detection and tracking of low contrast human sperm tail. Automation Science and Engineering (CASE), 2010 IEEE Conference on; 2010: IEEE.
Shi LZ, Nascimento J, Chandsawangbhuwana C, Berns MW, Botvinick EL. Real-time automated tracking and trapping system for sperm. Microsc Res Tech. 2006 Nov;69(11):894–902.
Abbiramy V, Shanthi V, Allidurai C, editors. Spermatozoa detection, counting and tracking in video streams to detect asthenozoospermia. Signal and Image Processing (ICSIP), 2010 International Conference on; 2010:IEEE.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Mohapatra, S.K., Mahapatra, S.K., Mahapatra, S., Sahoo, S.K., Ray, S., Dash, S.R. (2017). A Novel Approach for Tracking Sperm from Human Semen Particles to Avoid Infertility. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining. Advances in Intelligent Systems and Computing, vol 556. Springer, Singapore. https://doi.org/10.1007/978-981-10-3874-7_38
Download citation
DOI: https://doi.org/10.1007/978-981-10-3874-7_38
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-3873-0
Online ISBN: 978-981-10-3874-7
eBook Packages: EngineeringEngineering (R0)