An optimized transfer learning-based approach for automatic diagnosis of COVID-19 from chest x-ray images

Abstract

Accurate and fast detection of COVID-19 patients is crucial to control this pandemic. Due to the scarcity of COVID-19 testing kits, especially in developing countries, there is a crucial need to rely on alternative diagnosis methods. Deep learning architectures built on image modalities can speed up the COVID-19 pneumonia classification from other types of pneumonia. The transfer learning approach is better suited to automatically detect COVID-19 cases due to the limited availability of medical images. This paper introduces an Optimized Transfer Learning-based Approach for Automatic Detection of COVID-19 (OTLD-COVID-19) that applies an optimization algorithm to twelve CNN architectures to diagnose COVID-19 cases using chest x-ray images. The OTLD-COVID-19 approach adapts Manta-Ray Foraging Optimization (MRFO) algorithm to optimize the network hyperparameters’ values of the CNN architectures to improve their classification performance. The proposed dataset is collected from eight different public datasets to classify 4-class cases (COVID-19, pneumonia bacterial, pneumonia viral, and normal). The experimental result showed that DenseNet121 optimized architecture achieves the best performance. The evaluation results based on Loss, Accuracy, F1-score, Precision, Recall, Specificity, AUC, Sensitivity, IoU, and Dice values reached 0.0523, 98.47%, 0.9849, 98.50%, 98.47%, 99.50%, 0.9983, 0.9847, 0.9860, and 0.9879 respectively.

A Review Study of the Deep Learning Techniques used for the Classification of Chest Radiological Images for COVID-19 Diagnosis

“…They employed various classical Deep Learning architectures with transfer learning and make a comparison about the networks’ performance. Other researchers preferred to use transfer learning as an optimization part of their whole framework to further improve the effects ( ( El-Kenawy et al, 2021 ) ( Bashar et al, 2021 ) ( Bahgat et al, 2021 ) ( Baltazar et al, 2021 ) ( Lacerda et al, 2021 )).…”

“…Bahgat et al’s paper ( Bahgat et al, 2021 ) concentrated on hyperparameter optimization. They introduced an Optimized Transfer Learning-based Approach for Automatic Detection of COVID-19 (OTLD-COVID-19) to optimize the network hyperparameters’ for the CNN architecture.…”

“…(Rahman et al, 2020) Menon et al ( Menon et al, 2020 ) Dec-20 Chest X-Ray Chest X-Ray Images (Pneumonia)(Mooney P. 2020) COVID-19 image data collection (Cohen et al, 2020) COVID-19 Image Data Collection: Prospective Predictions Are the Future (Cohen et al, 2020) Elkenawy et al ( El-Kenawy et al, 2021 ) Feb-21 Chest X-Ray Labeled Optical Coherence Tomography (OCT) and Chest X-Ray Images for Classification. Mendeley Data, V2 (Kermany et al, 2018) COVID-19 image data collection (Cohen et al, 2020) Baltazar et al ( Baltazar et al, 2021 ) Feb-21 Chest X-Ray The Medical City Institutional Review Board (TMC IRB) Bahgat et al ( Bahgat et al, 2021 ) Mar-21 Chest X-Ray COVID-19 image data collection (Cohen et al, 2020) Pneumonia (virus) Vs. COVID-19 (Mahasin, 2020) COVID-19 X-ray images using CNN (Srikar, 2020). COVID-19 X-ray Images (Das, 2020).…”

PancreaSys: An Automated Cloud-Based Pancreatic Cancer Grading System

“…The transfer learning approach makes DL very robust to many different applications. For example, during this pandemic, DL is able to provide early detection of COVID-19-positive cases using an optimized transfer learning-based approach for quick treatment to prevent the spread (Bahgat et al, 2021). In pathological images, detection and classification of cancerous cells using DL has been widely used to extract relevant information such as morphology features on WSI to identify cancer conditions and classify them into binary or multiple classes (Bhatt et al, 2021).…”

An automated diagnosis and classification of COVID-19 from chest CT images using a transfer learning-based convolutional neural network

“…Fig. 3 shows four common methods for detecting COVID-19 [ 5 ]. The swab-based reverse transcription-polymerase chain reaction (RT-PCR) is the accepted standard screening strategy known as a microbiological test for diagnosing the presence of COVID-19.…”