Last Updated: 01/10/2025

Development of malaria and tuberculosis diagnostic devices using AI analysis of ultra-wide-field microscope images

Objectives

The main aim of this study is to establish a simple and quick method to photograph malaria parasites using an ultra-widefield fluorescence microscope and develop image analysis software using artificial intelligence through machine learning.

Principal Institution

National Institute of Advanced Industrial Science and Technology (AIST), Japan

Principal Investigators / Focal Persons

Muneaki Hashimoto

Rationale and Abstract

Malaria is diagnosed by microscopic observation of blood smears, but there is an overwhelming shortage of such experts. The device to photograph malaria parasite will also be able to test for tuberculosis, which overlaps with other endemic areas. This research will enable accurate, highly sensitive quantitative testing using the same device even by non-experts in malaria and tuberculosis endemic areas, which is expected to not only reduce the number of deaths from these infectious diseases, but also greatly contribute to preventing the spread of infection and the emergence of drug-resistant bacteria.

External reference

Project details

Themes

Diagnostics
Enabling Technologies & Assays
Health Systems

Date

Apr 2024 — Mar 2027

Total Project Funding

$30,043

Funding Details

Japan Society for the Promotion of Science (JSPS), Japan

Grant ID: 24K11667

JPY 4.55M