Elastic light scattering for low cost and non-destructive clinical pathogens identification

LUMINT will be an innovative tool using light scattering technology and AI to identify pathogens rapidly. A successful proof of concept has already been conducted, based on analysis in the lab of 10 frequent bacteria species. The LUMINT@CLINICS project aims to translate the tool to the clinical level.


In the modern world, bacteria and viruses resistant to antimicrobials are an increasing problem. When it comes to identifying rapidly multiplying bacteria, time is of the essence. The identification of bacteria is crucial for optimal therapy, and speedy and reliable diagnostics are at the heart of the fight against resistant superbugs.

EIT Health Lumint


The team consists of experts in fields of clinical microbiology, bioimaging and biomedical optics, diagnosis, and machine learning. The partners of the project are Ghent University, Assistance Publique -Hopitaux De Paris and Atomic Energy and Alternative Energies Commission.

The project

LUMINT is being developed as an innovative bacteria identification tool based on elastic light scattering technology and artificial intelligence (AI). When a cell is illuminated, it scatters light in a specific pattern. Elastic light scattering technology can be used to illuminate cells, and AI makes it possible to identify and compare the resulting light patterns. This can allow for faster identification of bacteria.

LUMINT will enter the microbiology analysis sector with the ability to compete with Maldi-TOF Mass spectrometry analysers by offering a low-cost, non-destructive and high performance solution.

The LUMINT solution can potentially have a huge impact on the organisation of microbiology labs. To be successful, the tool must be convincing in comparison with the current gold standards. To this end, the project will establish a communication and dissemination plan, based in particular on the expected organisational impact, the identified assets and barriers to adoption. In addition, the project will explore the opportunity, with other EIT Health projects, to establish and design a dedicated training programme on the use of artificial intelligence for diagnostics.


LUMINT will revolutionise processes at microbiological labs, as it will perform faster, non-destructive, fully automated analysis – and facilitate chain identification and antibiotic susceptibility testing. Healthcare professionals benefit from an improved ability to detect bacteria quickly, and patients and society will benefit from the resulting reduction in the spread of diseases.

Why this is an EIT Health project

This project is in keeping with th EIT Health Focus Area of improving “Care Pathways”, because it promises more rapid identification of a health threat, thereby allowing for better prevention and improved medical care.

Pierre Marcoux
| Senior researcher | CEA