ArticleJournal of applied clinical medical physics2021
A bibliometric of publication trends in medical image segmentation: Quantitative and qualitative analysis.
Article in Journal of applied clinical medical physics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review of artificial intelligence methods for detection and segmentation of unruptured intracranial aneurysms using medical imaging.Medical & biological engineering & computing · 2025Pooled it
- Recent trends in medical image segmentation and volumetric analysis in human studies (2000-2025): a bibliometric review.Surgical and radiologic anatomy : SRA · 2026Review
- Quality versus quantity of training datasets for artificial intelligence-based whole liver segmentation.medRxiv : the preprint server for health sciences · 2026Article
- Deep learning-based object detection algorithms in medical imaging: Systematic review.Heliyon · 2025Review
- Indian research on generative artificial intelligence in healthcare imaging: A comprehensive bibliometric analysis.Journal of clinical imaging science · 2025Article
- NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions.International journal of radiation oncology, biology, physics · 2024Article
- A bibliometric analysis of insomnia in adolescent.Frontiers in psychiatry · 2023Article
- Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.PloS one · 2023Article
- Knowledge domain and hotspots concerning photosensitive hydrogels for tissue engineering applications: A bibliometric and visualized analysis (1996-2022).Frontiers in bioengineering and biotechnology · 2022Article
- A bibliometric of publication trends in medical image segmentation: Quantitative and qualitative analysis.Journal of applied clinical medical physics · 2021Article
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Authors and funding
6 authors.
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Abstract
purposeMedical 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.
methodsThis 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.
resultsThe 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.
conclusionsThrough 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.