Coronavirus Pneumonia Classification Using X-Ray and CT Scan Images With Deep Convolutional Neural Network Models
Author:
Affiliation:
1. LABAB Laboratory, National Polytechnic School of Oran - Maurice Audin, Algeria
2. National Polytechnic School of Oran, Algeria
3. TechCICO Laboratory, University of Technology of Troyes, France
Abstract
Pneumonia is a life-threatening infectious disease affecting one or both lungs in humans. There are mainly two types of pneumonia: bacterial and viral. Likewise, patients with coronavirus can develop symptoms that belong to the common flu, pneumonia, and other respiratory diseases. Chest X-rays are the common method used to diagnose coronavirus pneumonia and it needs a medical expert to evaluate the result of X-ray. Furthermore, DL has garnered great attention among researchers in recent years in a variety of application domains such as medical image processing, computer vision, bioinformatics, and many others. In this paper, we present a comparison of Deep Convolutional Neural Networks models for automatically binary classification query chest X-ray & CT images dataset with the goal of taking precision tools to health professionals based on fined recent versions of ResNet50, InceptionV3, and VGGNet. The experiments were conducted using a chest X-ray & CT open dataset of 5856 images and confusion matrices are used to evaluate model performances.
Publisher
IGI Global
Subject
General Computer Science
Reference57 articles.
1. Characterization of coronary artery pathological formations from OCT imaging using deep learning
2. Deep Convolutional Neural Networks for Chest Diseases Detection
3. A Deep Learning Based Approach towards the Automatic Diagnosis of Pneumonia from Chest Radio-Graphs
4. Optimized CNN-based Diagnosis System to Detect the Pneumonia from Chest Radiographs
5. Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks
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