A Bibliometric of Publication Trends in Medical Image Segmentation: Quantitative and Qualitative Analysis

Journal of Applied Clinical Medical Physics, pp. 1-21, 2021

22 Pages Posted: 8 Oct 2021

See all articles by Bin Zhang

Bin Zhang

Baoji University of Arts and Sciences

Bahbibi Rahmatullah

Sultan Idris Education University

Shir Li Wang

Sultan Idris Education University

Guangnan Zhang

Baoji University of Arts and Sciences

Huan Wang

Baoji University of Arts and Sciences

Nader Ale Ebrahim

University of Malaya (UM) - Department of Engineering Design and Manufacture; Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM)

Date Written: August 28, 2021

Abstract

Purpose: Medical images are important in diagnosing disease and treatment planning. Computer algorithms that describe anatomical structures that highlight regions of interest and remove unnecessary information are collectively known as medical image segmentation algorithms. The quality of these algorithms will directly affect the performance of the following processing steps. There are many studies about the algorithms of medical image segmentation and their applications, but none involved a bibliometric of medical image segmentation.

Methods: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.

Results: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.

Conclusions: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.

Note:
Funding Information: None to declare.

Declaration of Interests: None to declare.

Keywords: bibliometric, image segmentation, medical image, publication trends, research productivity

JEL Classification: L11, L1, L2, M11, M12, M1, M54, Q1, O1, O3, P42, P24, P29, Q31, Q32, L17

Suggested Citation

Zhang, Bin and Rahmatullah, Bahbibi and Li Wang, Shir and Zhang, Guangnan and Wang, Huan and Ale Ebrahim, Nader and Ale Ebrahim, Nader, A Bibliometric of Publication Trends in Medical Image Segmentation: Quantitative and Qualitative Analysis (August 28, 2021). Journal of Applied Clinical Medical Physics, pp. 1-21, 2021, Available at SSRN: https://ssrn.com/abstract=3917563 or http://dx.doi.org/10.2139/ssrn.3917563

Bin Zhang

Baoji University of Arts and Sciences ( email )

Baoguang Rd
Shaanxi
Baoji, Weibin
China

Bahbibi Rahmatullah

Sultan Idris Education University

Tanjong Malim
Perak Darul Ridzuan
Proton City, Tg. Malim, Perak 35900
Malaysia

Shir Li Wang

Sultan Idris Education University ( email )

Tanjong Malim
Perak Darul Ridzuan
Proton City, Tg. Malim, Perak 35900
Malaysia

Guangnan Zhang

Baoji University of Arts and Sciences ( email )

Baoguang Rd
Shaanxi
Baoji, Weibin
China

Huan Wang

Baoji University of Arts and Sciences ( email )

Baoguang Rd
Shaanxi
Baoji, Weibin
China

Nader Ale Ebrahim (Contact Author)

Centre for Research Services, Institute of Management and Research Services (IPPP), University of Malaya (UM) ( email )

Kuala Lumpur, Wilayah Persekutuan 50603
University of Malaya (UM)
Kuala Lumpur, Wilayah Persekutuan 50603
Malaysia

HOME PAGE: http://https://umresearch.um.edu.my/

University of Malaya (UM) - Department of Engineering Design and Manufacture ( email )

Kuala Lumpur, 50603
Malaysia

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