Toward Clinical Applications of Intelligent Robotic Ultrasound Systems

The Robotic Ultrasound System (RUSS) has the potential to transform medical imaging by addressing limitations such as operator dependency, diagnostic variability, and reproducibility in traditional ultrasound (US) examination. Despite rapid technological advancements, a substantial gap remains between RUSS research progress and clinical adoption. This review examined the clinical roles and engineering advances of RUSS, identifying key barriers to translation. Clinically, it evaluated the current applications of RUSS in supporting US procedures, while from an engineering standpoint, it summarized recent innovations and remaining technical challenges. This review examined the current state-of-the-art RUSS technologies, categorizing them based on diverse organ-specific applications while also analyzing their core functional capabilities. This review revealed a focus disparity: while abdominal US is the most commonly used in clinical practice, vascular-targeted RUSS dominates current research. It also highlighted a misalignment between research priorities and actual clinical tasks. Current studies predominantly focused on autonomous scanning and imaging, with limited attention to downstream tasks such as disease diagnosis and analysis. Building on these observations, it identified critical challenges and future trends in RUSS development. This work provides a foundation for future research, fostering collaboration between clinicians and engineers to accelerate the translation of next-generation RUSS from bench to bedside.

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Publication Details

Journal
IEEE Reviews in Biomedical Engineering
Published
2025-10-02
DOI
https://doi.org/10.1109/rbme.2025.3610605
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
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article

Toward Clinical Applications of Intelligent Robotic Ultrasound Systems

Hongen Liao, Guochen Ning, Fang Chen, Zhongliang Jiang et al.
IEEE Reviews in Biomedical Engineering
Soft Robotics and Applications
article

Toward Clinical Applications of Intelligent Robotic Ultrasound Systems

Hongen Liao, Guochen Ning, Fang Chen, Zhongliang Jiang, Yan Kang, Jianwen Luo, Taiyu Han, Hanying Liang, Zihan Li
article en

Abstract

The Robotic Ultrasound System (RUSS) has the potential to transform medical imaging by addressing limitations such as operator dependency, diagnostic variability, and reproducibility in traditional ultrasound (US) examination. Despite rapid technological advancements, a substantial gap remains between RUSS research progress and clinical adoption. This review examined the clinical roles and engineering advances of RUSS, identifying key barriers to translation. Clinically, it evaluated the current applications of RUSS in supporting US procedures, while from an engineering standpoint, it summarized recent innovations and remaining technical challenges. This review examined the current state-of-the-art RUSS technologies, categorizing them based on diverse organ-specific applications while also analyzing their core functional capabilities. This review revealed a focus disparity: while abdominal US is the most commonly used in clinical practice, vascular-targeted RUSS dominates current research. It also highlighted a misalignment between research priorities and actual clinical tasks. Current studies predominantly focused on autonomous scanning and imaging, with limited attention to downstream tasks such as disease diagnosis and analysis. Building on these observations, it identified critical challenges and future trends in RUSS development. This work provides a foundation for future research, fostering collaboration between clinicians and engineers to accelerate the translation of next-generation RUSS from bench to bedside.

IEEE Reviews in Biomedical EngineeringVol. 19
Shenzhen University (CN), Shanghai Jiao Tong University (CN), Shenzhen Technology University (CN), Beijing Tsinghua Chang Gung Hospital (CN), Technical University of Munich (DE), Tsinghua University (CN)
Openalex Percentile: Top 74%
Soft Robotics and Applications
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