Novel approaches for classification COVID-19 and pneumonia disease from CT scans using radiomics features
by Linda Ait Mohammed; Fatiha Alim-Ferhat; Mohammed Abdelaziz
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 44, No. 2, 2024

Abstract: COVID-19 is a highly infectious and fatal pneumonia-like disease. Despite the time-consuming nature of RT-PCR (reverse transcription-polymerase chain reaction), it remains a proven testing method for detecting coronavirus infection. Therefore, COVID-19 screening can be adopted using X-ray and computed tomography (CT) images of an individual's lungs to assist the traditional RT-PCR method in making an accurate clinical diagnosis. This imaging-based diagnosis will facilitate the detection of coronavirus infection and provide insight into the status of the disease, its form, and its degree of risk to the patient's life. CT scanning has become the benchmark test for COVID-19 and other pneumonia diseases. It allows visualisation and precise localisation of lesions in the lungs and branches. This study aims to classify COVID-19 among other types of pneumonia using a new preprocessing method, a set of parameters relevant to matching the random forest model, and a hybrid segmentation method based on level set and morphological tools. With an accuracy of 98.30%, an AUC of 0.98 for classification, and a dice score of 76% for segmentation, this method yielded promising results comparable to those found in the literature and allowed automatic and accurate deferral between COVID-19 and other pneumonia infections.

Online publication date: Thu, 29-Feb-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biomedical Engineering and Technology (IJBET):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com