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Related Experiment Video

Updated: Jun 2, 2025

Measuring Sperm Guidance and Motility within the Caenorhabditis elegans Hermaphrodite Reproductive Tract
10:07

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Multidimensional morphological analysis of live sperm based on multiple-target tracking.

Hao Yang1, Mengmeng Ma1, Xiangfeng Chen2,3,4

  • 1Department of Assisted Reproduction, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China.

Computational and Structural Biotechnology Journal
|January 13, 2025
PubMed
Summary

This study introduces a deep learning framework for automated sperm analysis, improving accuracy and efficiency in evaluating sperm motility and morphology for assisted reproduction.

Keywords:
Deep learningLive spermMorphological analysisMotilityMultiple sperm trackingNon-staining

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Area of Science:

  • Biomedical Engineering
  • Artificial Intelligence in Medicine
  • Reproductive Biology

Background:

  • Manual semen evaluation is subjective and inefficient.
  • Current methods hinder advancements in assisted reproductive technologies (ART).
  • There is a need for objective, automated sperm analysis.

Purpose of the Study:

  • To develop a deep learning framework for non-invasive, multidimensional analysis of live sperm in motion.
  • To enhance current clinical sperm morphology testing.
  • To contribute to the advancement of ART.

Main Methods:

  • Improved FairMOT tracking algorithm with enhanced cost function for sperm head movement analysis.
  • Utilized BlendMask for individual sperm segmentation and SegNet for morphological component separation.
  • Validated the system on 1272 samples from multiple tertiary hospitals.

Main Results:

  • Achieved 90.82% morphological accuracy confirmed by experienced physicians.
  • Demonstrated high consistency between automated system results and manual microscopy.
  • Successfully realized simultaneous automated detection of sperm progressive motility and morphology.

Conclusions:

  • The deep learning framework offers an objective and efficient alternative to manual semen evaluation.
  • This technology can significantly improve sperm selection for procedures like intracytoplascitc sperm injection (ICSI).
  • The system advances automated sperm analysis for improved ART outcomes.