Scientometric Analysis of Image Processing in Relation to Covid-19 Detection

Abstract

 The study examines global literature on “Scientometric analysis of image processing in relation to Covid-19 Detection”. Various bibliometrics and scientometrics tools like VOSViewer and Biblioshiny are used to analyse the extensive bibliographic metadata (research articles, case study, reports and review articles) which was retrieved from Web of Science core collection database for detecting Covid-19 using image processing techniques This research work demonstrates the rapid increase of Covid-19 during 2020-22 . It considered 606 documents published in 333 sources by 3668 authors from 78 different countries. The citations for different countries, co-citations for the different sources, cooccurrence of keywords, and co-authorship of the countries were determined. Further, it was found that only 3 out of 78 countries were responsible for contributing more on detection of Covid-19 using image processing related research output. These findings are critical for academics, clinicians, journal editors, and those engaged in Covid-19 detection using image processing research to understand the present literature’s strengths and potential gaps, as well as to plan future data collection and science policy investments.