AI-Assisted Smartphone Microscopy

AI-Assisted Smartphone Microscopy

Water-borne diseases due to parasites such as Giardia and Cryptosporidium are still an important problem in Low-Income Countries like Nepal. Traditionally, detection of these parasites is done using a brightfield microscope which is expensive and not so portable for rural areas. Our collaborating partner institute KIAS1 has developed a smartphone microscope that is portable and available at a very low cost. However, manual identification and counting of cysts is tedious and error-prone when testing a large number of samples and takes some time to train a new user.

We are developing ML-based automated parasite detection algorithms that will allow us to reliably test a large number of samples in a short period of time without the need for an experienced user.

1 Shrestha, R., Duwal, R., Wagle, S., Pokhrel, S., Giri, B., & Neupane, B. B. (2020). A smartphone microscopic method for simultaneous detection of (oo) cysts of Cryptosporidium and Giardia. PLOS Neglected Tropical Diseases14(9), e0008560.     

Research Themes: Transforming Global Health with Affordable & Inclusive AI
Project Category: Computer Vision, Medical Imaging