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Related Concept Videos

Sperm Structure and Semen Composition01:22

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During ejaculation, males release around 2-5 milliliters of semen, which is a complex mixture of mature sperm and various fluids produced by accessory glands. The mature sperm cells measure approximately 60 micrometers in length and consist of a head, neck, midpiece, and tail. The head is flattened and tapered, measuring about 4 to 5 micrometers in length. It contains a nucleus with condensed chromosomes and an acrosome, a cap-like structure filled with enzymes essential for penetrating the...
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Spermatogenesis is the process by which haploid sperm cells are produced in the male testes. It starts with stem cells located close to the outer rim of seminiferous tubules. These spermatogonial stem cells divide asymmetrically to give rise to additional stem cells (meaning that these structures “self-renew”), as well as sperm progenitors, called spermatocytes. Importantly, this method of asymmetric mitotic division maintains a population of spermatogonial stem cells in the male...
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Related Experiment Video

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Gold-standard and improved framework for sperm head segmentation.

Violeta Chang1, Jose M Saavedra2, Victor Castañeda3

  • 1Department of Computer Science, University of Chile, Beauchef 851, 4th Floor, Santiago, Chile; Laboratory for Scientific Image Analysis (SCIAN-Lab), Centro de Espermiograma Digital Asistido por Internet (CEDAI SpA), Biomedical Neuroscience Institute (BNI), Program of Anatomy and Developmental Biology (ICBM), Faculty of Medicine, University of Chile, Independencia 1027, Santiago, Chile.

Computer Methods and Programs in Biomedicine
|July 23, 2014
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method for precise sperm head detection and segmentation, crucial for evaluating male infertility. The new technique significantly improves accuracy and reduces errors compared to existing methods.

Keywords:
Acrosome segmentationInfertilityMorphological analysisNucleus segmentationSperm head detectionSperm head segmentation

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Area of Science:

  • Biomedical Engineering
  • Reproductive Medicine
  • Computer Vision

Background:

  • Accurate semen analysis is vital for diagnosing male infertility.
  • Sperm morphology assessment requires precise detection and segmentation of sperm components.
  • Existing methods often lack objectivity and automation in sperm analysis.

Purpose of the Study:

  • To develop an improved, fully automatic two-stage framework for detecting and segmenting human sperm heads, including acrosome and nucleus.
  • To enhance the accuracy and objectivity of sperm morphological analysis.
  • To establish a gold-standard dataset for comparative analysis of sperm detection and segmentation methods.

Main Methods:

  • A two-stage framework utilizing k-means, mathematical morphology, clustering, and histogram statistical analysis.
  • Integration of three different color spaces for improved feature detection.
  • Development of a gold-standard dataset with expert collaboration for validation.

Main Results:

  • Achieved over 98% accuracy in sperm head detection with significantly fewer false positives than state-of-the-art methods.
  • Demonstrated accurate segmentation of sperm head, acrosome, and nucleus with over 80% overlap against the gold standard.
  • Outperformed existing methods in key evaluation metrics like Dice coefficient and Hausdorff distance.

Conclusions:

  • The proposed automated framework offers a significant advancement in objective and accurate semen analysis.
  • This method has the potential to improve the diagnostic capabilities for infertile couples.
  • The developed gold-standard dataset facilitates future research and validation in sperm cell analysis.