Mapping the Literature on the Application of Image Processing in the Medical Field: A Scientometric Analysis

Abstract

The application of image processing in the Medical field has witnessed remarkable growth and innovation. This scientometric analysis delves into the vast body of literature that explores this intersection, aiming to map the landscape of research and development in this crucial domain. Our research uses scientometric approaches to analyze and synthesize a large corpus of scientific publications, including journal articles, conference papers, and patents. We investigate major trends, notable study topics, influential authors, and the growth of knowledge networks. The study was designed using a scientometric approach, with data extracted from a renowned database, Web of Sciences, from 2004 to 2023. A total of 1723 journals and conference proceedings from Web of Science database were analyzed. Trends within the field are identified, as are the dominant sub-fields and their interconnections, as well as citation patterns, key publications, key research institutions, key researchers, and key journals, along with the extent to which these interact with each other in research networks. The stages are as follows: (1) identification, keyword selection, and formation of the search strategy with the permission of a panel of computer scientists and librarians; and (2) design and construction of a flawless algorithm to validate these selected keywords in Web of Science title-abstract-keywords. (3) Processing data in certain cutting-edge bibliometric visualization tools, Biblioshiny R and VOSviewer (4) analyzing the findings for practical consequences.

This study's findings shed light on the critical significance of image processing in Medical research and clinical practice. Our study contributes to a greater understanding of the contributions and difficulties within this dynamic junction of technology and healthcare by recognizing emerging subfields, significant research, and the interplay between many disciplines. This scientometric investigation provides insights that can help researchers, policymakers, and industry experts navigate the changing landscape of Medical image processing, ultimately leading to breakthroughs that benefit both healthcare practitioners and patients.