The Mini-Hematology-Lab project addresses the challenges of traditional blood analysis in field and remote labs, particularly in developing regions where conventional flow cytometry is often too expensive and difficult to maintain. As an affordable, AI-powered alternative, this mini-lab utilizes a 3D-printable robotic microscope with advanced machine-learning to analyze blood samples with high speed and accuracy.
How It Works: Manual microscopy has long been the gold standard for diagnosing diseases by visually identifying blood cells. However, it is time-consuming and prone to human error, especially when performed over long hours. This project adapts AI technology, similar to that used in self-driving cars, to automatically identify and count blood cells, improving both accuracy and efficiency.
The Mini-Hematology-Lab is built on the OpenFlexure robotic microscope platform, with modifications that enable it to detect parasites like malaria and perform blood counts on red and white blood cells at a rate of 1.5 million cells per minute—120 times faster than manual methods. The setup cost for this lab is under $350, making it a cost-effective and accessible solution.
Key Features:
- Red Blood Cell (RBC) count
- White Blood Cell (WBC) count
- Differential WBC count
- Platelet count
- Parasite detection (e.g., malaria)
- USB battery-powered for use in the field
- Low-cost and open-source design
Progress Updates:
- Microscope design modifications – Complete (2021-09-01)
- Motor controller board design – Complete (2021-10-01)
- Blood staining protocol and wiki documentation – Complete (2021-10-04)
- Software for AI hematology and malaria – In development
- Full documentation – In progress
Credit: This project extends the OpenFlexure microscope, initially created by Richard Bowman and maintained by the Bath Open Instrumentation Group, with further adaptations by WoIdMo for diagnostic use in remote and resource-limited settings.
