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Please use this identifier to cite or link to this item: https://repository.esi-sba.dz/jspui/handle/123456789/380
Title: D´etection du COVID-19 par r´eseaux convolutionnels et `a l’aide des images radiologiques (X-rays)
Authors: BELLAOUEDJ, ISmail
Keywords: Deep Learning
Convolutional Neural Networks
Covid-19 Detection
Transfer Learning Transfer
Issue Date: 2022
Abstract: Currently, several studies are discussing the detection of lung diseases by analyzing medical images using deep learning. Deep learning is also a valuable aid to experts in the interpretation of medical images. Heuristics such as transfer learning (a deep learning method where a model developed for a given task is reused as a starting point for another model that targets a second task) is emerging. These approaches (based on pre-trained models) are used as the starting point for computer vision tasks and can offer considerable gains to many problems. In this project, we propose Convolutional Neural Networks (CNN) models to detect the presence of COVID-19 in X-ray images. As an additional contribution, we show the layers of the network, i.e. the areas of the chest X-ray that the model considered for generating the prediction; this can ultimately be presented as a suggestion for the radiologist in the suspect area. *** Actuellement, plusieurs ´etudes discutent la d´etection des maladies pulmonaires en analysant images m´edicales en exploitant l’apprentissage profond (deep learning).Ce dernier constitue aussi une aide pr´ecieuse aux experts pour l’interpr´etation des images m´edicales. Des heuristiques telles que l’apprentissage par transfert(une m´ethode d’apprentissage profond o`u un mod`ele d´evelopp´e pour une tˆache est r´eutilis´e comme point de d´epart d’un mod`ele sur une seconde tˆache) est en train d’´emerger. Ces approches `a base de mod`eles pr´e-entraˆın´es sont utilis´es comme le point de d´epart des tˆaches de vision par ordinateur et peuvent leur assurer d’ ´enormes gains. Nous proposons dans ce projet des mod`eles de type R´eseau neuronal `a convolution pour d´etecter la pr´esence de COVID-19 dans les images rayons X. Comme contribution suppl´ementaire, nous montrons les couches d’activation du r´eseau, c’est-`a-dire les zones de la radiographie pulmonaire que le mod- `ele a consid´er´e pour g´en´erer la pr´ediction, Cela peut repr´esenter une suggestion pour le radiologue de la zone suspecte.
Description: Encadreur : Mr HADJILA Fethallah Co-Encadreur : Mr AMAR BENSABER Djamel
URI: https://repository.esi-sba.dz/jspui/handle/123456789/380
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