BloodBox: A Diagnostic Tool For Blood-Borne Diseases
The Project
BloodBox is a diagnostic tool for blood borne diseases which takes a magnified image of blood cells using a raspberry pi and camera. The image is then processed by a Tensorflow Lite machine learning model on the pi. We use image classification models to detect malaria and leukaemia in individual cells. We also use an object detection model based on the YOLO Framework to return a Complete Blood Cell Count report. We 3D printed parts for this device ourselves.
About the team
Team members
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