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Hepatology International
Published in: Hepatology International 2/2024

20-02-2024 | Artificial Intelligence | Review Article

Artificial intelligence in liver imaging: methods and applications

Authors: Peng Zhang, Chaofei Gao, Yifei Huang, Xiangyi Chen, Zhuoshi Pan, Lan Wang, Di Dong, Shao Li, Xiaolong Qi

Published in: Hepatology International | Issue 2/2024

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Abstract

Liver disease is regarded as one of the major health threats to humans. Radiographic assessments hold promise in terms of addressing the current demands for precisely diagnosing and treating liver diseases, and artificial intelligence (AI), which excels at automatically making quantitative assessments of complex medical image characteristics, has made great strides regarding the qualitative interpretation of medical imaging by clinicians. Here, we review the current state of medical-imaging-based AI methodologies and their applications concerning the management of liver diseases. We summarize the representative AI methodologies in liver imaging with focusing on deep learning, and illustrate their promising clinical applications across the spectrum of precise liver disease detection, diagnosis and treatment. We also address the current challenges and future perspectives of AI in liver imaging, with an emphasis on feature interpretability, multimodal data integration and multicenter study. Taken together, it is revealed that AI methodologies, together with the large volume of available medical image data, might impact the future of liver disease care.
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Metadata
Title
Artificial intelligence in liver imaging: methods and applications
Authors
Peng Zhang
Chaofei Gao
Yifei Huang
Xiangyi Chen
Zhuoshi Pan
Lan Wang
Di Dong
Shao Li
Xiaolong Qi
Publication date
20-02-2024
Publisher
Springer India
Published in
Hepatology International / Issue 2/2024
Print ISSN: 1936-0533
Electronic ISSN: 1936-0541
DOI
https://doi.org/10.1007/s12072-023-10630-w

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