Abstract
Recently many studies have shown the effectiveness of using augmented reality (AR) and virtual reality (VR) in biomedical image analysis. However, they are not automating the COVID level classification process. Additionally, even with the high potential of CT scan imagery to contribute to research and clinical use of COVID-19 (including two common tasks in lung image analysis: segmentation and classification of infection regions), publicly available data-sets are still a missing part in the system care for Algerian patients. This article proposes designing an automatic VR and AR platform for the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic data analysis, classification, and visualization to address the above-mentioned challenges including (1) utilizing a novel automatic CT image segmentation and localization system to deliver critical information about the shapes and volumes of infected lungs, (2) elaborating volume measurements and lung voxel-based classification procedure, and (3) developing an AR and VR user-friendly three-dimensional interface. It also centered on developing patient questionings and medical staff qualitative feedback, which led to advances in scalability and higher levels of engagement/evaluations. The extensive computer simulations on CT image classification show a better efficiency against the state-of-the-art methods using a COVID-19 dataset of 500 Algerian patients. The developed system has been used by medical professionals for better and faster diagnosis of the disease and providing an effective treatment plan more accurately by using real-time data and patient information.
Highlights
Variants of COVID-19 have been reported ubiquitously world-wide, causing more infections and spreading faster than any previously known form of the virus [1]
Virtual reality and augmented reality have represented a breakthrough for healthcare professionals
The main contribution of this study is to develop an original approach for efficiently bringing together segmentation, classification, virtual and augmented reality with computerized tomography images for COVID-19 diagnostic aid
Summary
Variants of COVID-19 have been reported ubiquitously world-wide, causing more infections and spreading faster than any previously known form of the virus [1]. This raises the urgent need for developing effective and safe COVID-19 vaccines [2]. Reverse-transcription-polymerase-chain-reaction (RT-PCR) is a commonly used protocol in the detection and quantification of virus infections [6]. It is time-consuming and may provide both false-negative (FN) and false-positive (FP) rates [7]. In Algeria, CT scans have been widely used and show good clinical diagnostics [11].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
