  We report a field-portable and cost-effective imaging flow cytometer that
uses deep learning to accurately detect Giardia lamblia cysts in water samples
at a volumetric throughput of 100 mL/h. This flow cytometer uses lensfree color
holographic imaging to capture and reconstruct phase and intensity images of
microscopic objects in a continuously flowing sample, and automatically
identifies Giardia Lamblia cysts in real-time without the use of any labels or
fluorophores. The imaging flow cytometer is housed in an environmentally-sealed
enclosure with dimensions of 19 cm x 19 cm x 16 cm and weighs 1.6 kg. We
demonstrate that this portable imaging flow cytometer coupled to a laptop
computer can detect and quantify, in real-time, low levels of Giardia
contamination (e.g., <10 cysts per 50 mL) in both freshwater and seawater
samples. The field-portable and label-free nature of this method has the
potential to allow rapid and automated screening of drinking water supplies in
resource limited settings in order to detect waterborne parasites and monitor
the integrity of the filters used for water treatment.
