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Microbial identification is a critical process aiming at identifying the species contained in a biological sample, with applications in healthcare, industry or even national security. Traditionally, this process relies either on MALDI-TOF mass spectroscopy, on biochemical tests and on the observation of the morphology of colonies after growth on a Petri dish. Here is presented an innovative method for label-free optical identification of pathogens, based on the multispectral infrared imaging of colonies. This lensless imaging technique enables a high-throughput analysis and wide-field analysis of agar plates. It could yield very high correct identification rates as it relies on an optical fingerprint gathering both spectroscopic and morphologic features. The setup consists of a Quantum Cascade Lasers light source and an imager, a square 2.72 by 2.72 mm uncooled bolometer array. Microorganisms to be analyzed are streaked on a porous growth support compatible with infrared imaging, laid on top of an agar plate for incubation. When imaging is performed, growth support is put in close contact with the imaging sensor and illuminated at different wavelengths. After acquisition, an image descriptor based on spectral and morphological features is extracted for each microbial colony. Supervised classification is finally performed with a Support Vector Machine algorithm and tested with tenfold cross-validation. A first database collecting 1012 multispectral images of colonies belonging to five different species has already been acquired with this system, resulting in a correct identification rate of 92%. For these experiments, multispectral images are acquired at nine different wavelengths, between 5.6 and 8 μm. Considering the optimization possibilities of the image descriptors currently used and the ongoing development of the uncooled bolometers technology, these very first results are promising and could be dramatically improved with further experiments. Thereby, mid-infrared multispectral lensless imaging has the potential to become a fast and precise Petri dish analysis technology.
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