COVI³D: Automatic COVID-19 CT Image-Based Classification and Visualization Platform Utilizing Virtual and Augmented Reality Technologies

Round 1

Reviewer 1 Report

 

The manuscript diagnostics-1608960, entitled “COVI3D: Automatic COVID-19 CT Image-based Classification and Visualization Platform Utilizing Virtual and Augmented Reality Technologies” by Samir Benbelkacem and coworkers.

They used Augmented Reality (AR) and Virtual Reality (VR) in the COVID classification process.

Using an automatic VR and AR platform for the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) pandemic data analysis, classification, and visualization. The extensive computer simulations on CT image classification show a better efficiency against the state-of-the-art methods using 500 Algerian patients COVID-19 dataset. The developed system has been used by medical professionals better and faster diagnose the disease and provide an effective treatment plan more accurately by using real-time data and patient information.

The experimental work is clear and well described.

Figure are informative

English is fine.

Author Response

We would like to thank the reviewer for the time spent on reviewing our manuscript and the comments helping us to improve the paper.

Point 1: We have performed some improvements in the “Conclusion” section (changes are given in the revised paper in red color).

Point 2: We made other changes in the acknowledgments, some authors' affiliation and correspondence.

Point 3: Please refer to the file: diagnostics-1608960- COVID-3D Classification and Visualization Platform.pdf

Reviewer 2 Report

The paper is well written and structured. This article present a design methodology of an automatic VR and AR platform for the SARS-CoV-2 pandemic data analysis, classification, and visualization to address different challenges challenges. 

I believe the authors can just add the limitation of the proposed scheme on the conclusion and highlight the future work.

 

Author Response

We would like to thank the reviewer for the time spent on reviewing our manuscript and the comments helping us to improve the paper.

Point 1:  we have performed some improvements in the “Conclusion” section (changes are given in the revised paper in red color).

Point 2:  responses according to the reviewer' comments are given in word file. Please see the attachment.  

Point 3: we made other changes in the acknowledgments, some authors' affiliation and correspondence.

Point 4: please refer to the file: diagnostics-1608960- COVID-3D Classification and Visualization Platform.pdf

Author Response File: Author Response.docx