cysts using holographic imaging flow-cytometry and deep learning*

Annually >200 million people contract giardiasis, a diarrheal illness caused by Giardia lamblia, a microscopic waterborne parasite. To provide a cost-effective water screening tool, we created a field-portable holographic imaging flow-cytometer that can acquire in-focus phase and amplitude images of microscopic objects in water samples with a half-pitch resolution of <2µm and a liquid throughput of 100 mL/h. This computational imaging cytometer is controlled by a laptop, which is used to segment and reconstruct all the microscopic objects within the flow and can in real-time identify and count Giardia lamblia cysts using a trained convolutional neural network, achieving a detection limit of <10 cysts per 50 mL. This unique device is cost effective, compact (19 × 19 × 16 cm), lightweight (1.6 kg) and is entirely label-free, making it highly suitable for testing of drinking water supplies or for monitoring the integrity of filters in water treatment systems.