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<dc:title xml:lang="en">Detection of microorganism colonies in sequences of high resolution images : early detection of antimicrobial resistance</dc:title>
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<dc:subject xml:lang="fr">Résistance aux antimicrobiens</dc:subject>
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<dcterms:abstract xml:lang="fr">La culture sur milieu gélosé peut être présente sous différentes formes dans l’étude d’échantillons microbiologiques, de la détection de pathogènes jusqu’à l’étude de la résistance de ces même pathogènes aux antibiotiques. Cependant c’est une méthode pouvant s’avérer fastidieuse est relativement lente. L’instrument Evisight que l’on utilise permet de prendre des images des boites de Pétri pendant l’incubation, autorisant ainsi l’utilisation de méthodes de traitement d’images, pour un résultat avant la fin de l’incubation. Nous développons une méthode d’apprentissage profond pour la détection de microorganismes, en image finale tout d’abord, puis en dans un second temps avec l’ensemble des images prises pendant l’incubation. Enfin une troisième étude a été mené afin d’automatiser la méthode de détection de résistance aux antibiotiques via culture sur gélose, mais également obtenir un meilleur temps avant résultat pour cette même méthode.</dcterms:abstract>
<dcterms:abstract xml:lang="en">The culture on agar medium can be present in various forms in the study of microbiological samples, from the detection of pathogens to the study of the resistance of these same pathogens to antimicrobials. However it is a method that can be tedious and relatively slow. The Evisight instrument used is able to take images of Petri dishes during incubation, thus allowing the use ofimage processing methods, for a result before the end of the incubation. We develop a deep learning method for the detection of microorganisms, in the final image first, then in a second step with all the images taken during the incubation. Finally, a third study was conducted to automate the method of antimicrobial resistance detection via agar culture, but also to obtain a better time beforeresult.</dcterms:abstract>
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