HEAD - YOLO Software

Precision Software for Accurate Identification and Analysis of Helminth Eggs in Diagnostic Samples

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Advanced Helminth Eggs Detection Solutions

Enhanced Detection Accuracy

Combines HEAD software and YOLO neural network for precise identification and quantification of helminth eggs, minimizing error sources and improving result reliability.

Local Installation

Software operates locally on Windows PCs, ensuring easy access and integration into existing workflows.

Comprehensive Species Coverage

Identifies and quantifies nine medically significant helminth species commonly found in environmental samples, including wastewater and soil.

Cost Efficiency

Reduces analytical costs while providing prompt and reliable detection, making advanced analysis accessible to a broader community.

Quality Monitoring

Facilitates better monitoring of environmental sample quality and treatment process performance through accurate helminth egg detection.

The Challenge

Globally, more than 2.5 billion people are affected by helminths (parasitic worms), mainly due to poor sanitation, the use of polluted water for irrigation, and the disposal to land of excreta or sludge. These parasitic worms are transmitted through their eggs. Even though criteria and regulations limit their concentration/limit their presence in environmental matrices exist, their application relies on the capacity to identify correctly these eggs by direct observation through a microscope.

This step is crucial since it is the main source of error as highly qualified technicians are needed to visually recognize them. As a result, compliance with such regulations does not always take place and the transmission of these parasites still occurs. The use of the Software HEAD-YOLO avoids these problems by identifying and quantifying nine different species of helminth eggs in images taken from environmental samples.

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Our Solution

HEAD - YOLO

HEAD-YOLO Software integrates the HEAD detection system with the YOLO neural network to accurately identify and quantify nine key helminth egg species in various environmental samples. Operating locally on Windows PCs, it enhances detection precision, reduces errors, and lowers analytical costs, improving monitoring and treatment processes.

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Species identified

  • Ascaris spp. (fertile and infertile)
  • Trichuris trichiura
  • Toxocara canis
  • Taenia saginata
  • Hymenolepsis diminuta
  • Hymenolepsis nana
  • Schistosoma mansoni
  • Fasciola hepatica
  • Fasciolopsis buski

How It Works

  • 1

    Image Input and Processing

  • 2

    Identification and Counting

  • 3

    Output Delivery

Research & Sponsor

This software is based on research funded in part by the Bill & Melinda Gates Foundation. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation.



You only look once (YOLO) neural network