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Related Experiment Video

Updated: Jan 10, 2026

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

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

Published on: June 6, 2019

Multi-object sperm detection and tracking based on enhanced YOLOv4 and improved DeepSORT.

Jihong Pei¹, Zhenting Yang¹, Yang Zhao²

¹College of Electronics and Information Engineering, Shenzhen University, ShenZhen, 518060, China.

Scientific Reports

|November 27, 2025

Summary

This summary is machine-generated.

This study introduces an advanced framework for computer-aided semen analysis, improving sperm detection and tracking in microscopic images. The enhanced system effectively handles small and indistinct sperm targets, advancing infertility diagnostics.

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Area of Science:

Biomedical Engineering
Computer Vision
Reproductive Medicine

Background:

Assisted reproductive technology is crucial for infertility treatment.
Current computer-aided semen analysis struggles with small and indistinct sperm images.
Accurate sperm analysis is vital for effective infertility solutions.

Purpose of the Study:

To develop an advanced multi-object sperm detection and tracking framework.
To overcome limitations in current computer-aided semen analysis systems.
To enhance the accuracy of sperm analysis for infertility diagnosis.

Main Methods:

Integration of an enhanced YOLOv4 architecture with an optimized DeepSORT algorithm.
Implementation of a novel image slicing strategy to prevent small target loss.
Utilizing ResNet50 for improved feature extraction and a specialized sperm image augmentation strategy.

Main Results:

Superior performance in sperm detection and tracking metrics.
Robust detection and tracking of multiple small sperm targets.
Outperformed existing state-of-the-art methods in accuracy and efficiency.

Conclusions:

The proposed framework significantly improves computer-aided semen analysis.
The system offers enhanced accuracy for detecting and tracking sperm, especially small targets.
This advancement holds promise for more effective infertility diagnostics and treatments.