Deep features to detect pulmonary abnormalities in chest X-rays due to infectious diseaseX: Covid-19, pneumonia, and tuberculosis

Explanatory classification of CXR images into COVID-19, Pneumonia and Tuberculosis using deep learning and XAI

“…DL model with nine hidden layers was proposed by Mahbub et al. [19] for CXR image classification. With the DL model trained from scratch, six different datasets derived from publicly available CXR images were employed for the binary classification of three disease classes: COVID-19, TB and Pneumonia.…”

“…They have created an opportunity for developing an intelligent and automated framework for image-based health care solutions [18] . For instance, multiple DL models in medical image analysis [15] , [19] , [20] , [21] have been proposed to learn powerful image features for the diagnosis of diseases thereby preventing severe sickness. Despite magnetic resonance imaging (MRI) and computerized tomography (CT) scan being more efficient in producing clear pictures, they are very expensive and contain radiation exposure.…”

“…DL-based methods have achieved high accuracy in CXR image classification [19] . However, these methods have three major limitations.…”

Deep viewing for the identification of Covid-19 infection status from chest X-Ray image using CNN based architecture

“…(2021) 2905 x-rays mAlexNet BiLSTM (Hybrid) architecture 97.70 Purohit et al. (2022) 5220 CT-scans Deep Learning 96.47 Bassi and Attux (2022) 2064 x-rays Deep CNN 99.02 Mahbub et al. (2022a) 1200 x-rays Customized DNN 97.87 Gaur et al.…”

COVID-Net CXR-2: An Enhanced Deep Convolutional Neural Network Design for Detection of COVID-19 Cases From Chest X-ray Images

“…While the initiative has been successful and leveraged globally, the continuously evolving nature of the pandemic and the increasing quantity of available CXR data from multinational cohorts has led to a growing demand for ever-improving computer-aided diagnostic solutions as part of the initiative. Since the launch of the COVID-Net open source initiative, there have been many studies in the area of COVID-19 case detection using CXR images (22)(23)(24)(25)(26)(27)(28)(29) emphasizing appropriate data curation and training regimes (30)(31)(32), with many leveraging the open access datasets and open source deep neural networks made publicly available through this initiative (33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49).…”