Tracking of human sperm in time-lapse images

Chizhong Wang, Ji Won Choi, Leonardo F. Urbano, Puneet Masson, Matthew Vermilyea, Moshe Kam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Human sperm motility analysis is a key method in assessing male fertility. It was suggested that performance of automatic sperm motility analysis systems can be enhanced by adopting multi-target tracking algorithms developed originally for radar technology. We review and appraise several target tracking algorithms operating on synthetic and actual sperm images and compare their performance. Simulations and observations of images of real sperm cells suggest that the joint probability data association filter with track-coalescence-avoiding (JPDA) outperforms other evaluated algorithms. This is also the result obtained on images of swimming tadpoles.

Original languageEnglish (US)
Title of host publication2018 IEEE 3rd International Conference on Signal and Image Processing, ICSIP 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages197-201
Number of pages5
ISBN (Electronic)9781538663943
DOIs
StatePublished - Jan 2 2019
Event2018 IEEE 3rd International Conference on Signal and Image Processing, ICSIP 2018 - Shenzhen, China
Duration: Jul 13 2018Jul 15 2018

Publication series

Name2018 IEEE 3rd International Conference on Signal and Image Processing, ICSIP 2018

Conference

Conference2018 IEEE 3rd International Conference on Signal and Image Processing, ICSIP 2018
Country/TerritoryChina
CityShenzhen
Period7/13/187/15/18

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Signal Processing

Keywords

  • Human sperm tracking
  • Performance evaluation
  • Sperm motility
  • Tracking algorithm

Fingerprint

Dive into the research topics of 'Tracking of human sperm in time-lapse images'. Together they form a unique fingerprint.

Cite this