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. 2022:2022:9841548.
doi: 10.34133/2022/9841548. Epub 2022 Jun 14.

Knowledge Graph Applications in Medical Imaging Analysis: A Scoping Review

Song Wang  1 , Mingquan Lin  2 , Tirthankar Ghosal  3 , Ying Ding  1 , Yifan Peng  2
Affiliations

Knowledge Graph Applications in Medical Imaging Analysis: A Scoping Review

Song Wang et al. Health Data Sci. 2022.

Abstract

Background: There is an increasing trend to represent domain knowledge in structured graphs, which provide efficient knowledge representations for many downstream tasks. Knowledge graphs are widely used to model prior knowledge in the form of nodes and edges to represent semantically connected knowledge entities, which several works have adopted into different medical imaging applications.

Methods: We systematically searched over five databases to find relevant articles that applied knowledge graphs to medical imaging analysis. After screening, evaluating, and reviewing the selected articles, we performed a systematic analysis.

Results: We looked at four applications in medical imaging analysis, including disease classification, disease localization and segmentation, report generation, and image retrieval. We also identified limitations of current work, such as the limited amount of available annotated data and weak generalizability to other tasks. We further identified the potential future directions according to the identified limitations, including employing semisupervised frameworks to alleviate the need for annotated data and exploring task-agnostic models to provide better generalizability.

Conclusions: We hope that our article will provide the readers with aggregated documentation of the state-of-the-art knowledge graph applications for medical imaging to encourage future research.

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Conflict of interest statement

Conflicts of Interest The authors declare no competing interests.

Figures

Figure 1
Figure 1
Radiology knowledge graph example: NIH Chest X-ray labels based on RadLex and SNOMED_CT.
Figure 2
Figure 2
The flowchart of the article selection process.
Figure 3
Figure 3
Year trend of reviewed articles.
Figure 4
Figure 4
Publication country distributions.
Figure 5
Figure 5
Application topic distributions.
See this image and copyright information in PMC

References

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