An Classification–Detection Approach of COVID-19 Based on Chest X-ray and CT by Using Keras Pre-Trained Deep Learning Models

Abstract

The Coronavirus Disease 2019 (COVID-19) is wreaking havoc around the world, bring out that the enormous pressure on national health and medical staff systems. One of the most effective and critical steps in the fight against COVID-19, is to examine the patient's lungs based on the Chest X-ray and CT generated by radiation imaging. In this paper, five keras-related deep learning models: ResNet50, InceptionResNetV2, Xception, transfer learning and pre-trained VGGNet16 is applied to formulate an classification-detection approaches of COVID-19. Two benchmark methods SVM (Support Vector Machine), CNN (Conventional Neural Networks) are provided to compare with the classification-detection approaches based on the performance indicators, i.e., precision, recall, F1 scores, confusion matrix, classification accuracy and three types of AUC (Area Under Curve). The highest classification accuracy derived by classification-detection based on 5857 Chest X-rays and 767 Chest CTs are respectively 84% and 75%, which shows that the keras-related deep learning approaches facilitate accurate and effective COVID-19-assisted detection.

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

“…Early diagnosis of COVID-19 is important to minimize human-to-human transmission and patient care. Recently, the separation and quarantine of healthy people from the infected or persons who suspect that they are carrying the virus is the most effective technique to avoid the spread of COVID-19 (Deng 2020). Machine-learning techniques role showed an important understandings of the COVID-19 diagnosis, such as lung computed tomography (CT) scan whether it can be regarded as the first screening or an alternative test for the real-time inverse transcriptase-polymerase chain reaction (RT-PCR), and the differences between COVID-19 pneumonia and other viral pneumonia using CT scan of the lungs (Kassani et al (2004)).…”

Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic

“…They reported that using the VGG16 technique gave the highest classification accuracy of 80% among the other four proposed models. The same procedure has been followed in [ 35 , 54 ]. The authors in [ 54 ] used five pre-trained models, including ResNet50, InceptionResNetV2, and Xception.…”

Analisis Perbandingan Algoritma Klasifikasi Citra Chest X-ray Untuk Deteksi Covid-19

“…Deng, et.al. [7] menggunakan pre-trained model Keras pada data Chest X-ray dan Chest CT. Akurasi yang dihasilkan dikedua dataset tersebut adalah 84% dan 75%. Performa yang dihasilkan tersebut masih memiliki akurasi di bawah 90%.…”

“…Dataset citra Chest X-ray yang digunakan pada kasus ini memiliki jumlah yang berbeda tiap kelas klasifikasinya seperti yang ada pada Tabel 1. Rumus perhitungan weighted metric dapat dilihat pada Persamaan (7).…”