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- Publisher Website: 10.1109/RBME.2025.3610605
- Scopus: eid_2-s2.0-105017760165
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Article: Toward Clinical Applications of Intelligent Robotic Ultrasound Systems
| Title | Toward Clinical Applications of Intelligent Robotic Ultrasound Systems |
|---|---|
| Authors | |
| Keywords | autonomy clinical applications medical robotics robot learning robotic ultrasound systems Ultrasound imaging |
| Issue Date | 2025 |
| Citation | IEEE Reviews in Biomedical Engineering, 2025 How to Cite? |
| 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. |
| Persistent Identifier | http://hdl.handle.net/10722/365365 |
| ISSN | 2023 Impact Factor: 17.2 2023 SCImago Journal Rankings: 3.099 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Han, Taiyu | - |
| dc.contributor.author | Ning, Guochen | - |
| dc.contributor.author | Liang, Hanying | - |
| dc.contributor.author | Li, Zihan | - |
| dc.contributor.author | Jiang, Zhongliang | - |
| dc.contributor.author | Chen, Fang | - |
| dc.contributor.author | Kang, Yan | - |
| dc.contributor.author | Luo, Jianwen | - |
| dc.contributor.author | Liao, Hongen | - |
| dc.date.accessioned | 2025-11-05T06:55:39Z | - |
| dc.date.available | 2025-11-05T06:55:39Z | - |
| dc.date.issued | 2025 | - |
| dc.identifier.citation | IEEE Reviews in Biomedical Engineering, 2025 | - |
| dc.identifier.issn | 1937-3333 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/365365 | - |
| dc.description.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. | - |
| dc.language | eng | - |
| dc.relation.ispartof | IEEE Reviews in Biomedical Engineering | - |
| dc.subject | autonomy | - |
| dc.subject | clinical applications | - |
| dc.subject | medical robotics | - |
| dc.subject | robot learning | - |
| dc.subject | robotic ultrasound systems | - |
| dc.subject | Ultrasound imaging | - |
| dc.title | Toward Clinical Applications of Intelligent Robotic Ultrasound Systems | - |
| dc.type | Article | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1109/RBME.2025.3610605 | - |
| dc.identifier.scopus | eid_2-s2.0-105017760165 | - |
| dc.identifier.eissn | 1941-1189 | - |
