File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Toward Clinical Applications of Intelligent Robotic Ultrasound Systems

TitleToward Clinical Applications of Intelligent Robotic Ultrasound Systems
Authors
Keywordsautonomy
clinical applications
medical robotics
robot learning
robotic ultrasound systems
Ultrasound imaging
Issue Date2025
Citation
IEEE Reviews in Biomedical Engineering, 2025 How to Cite?
AbstractThe 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 Identifierhttp://hdl.handle.net/10722/365365
ISSN
2023 Impact Factor: 17.2
2023 SCImago Journal Rankings: 3.099

 

DC FieldValueLanguage
dc.contributor.authorHan, Taiyu-
dc.contributor.authorNing, Guochen-
dc.contributor.authorLiang, Hanying-
dc.contributor.authorLi, Zihan-
dc.contributor.authorJiang, Zhongliang-
dc.contributor.authorChen, Fang-
dc.contributor.authorKang, Yan-
dc.contributor.authorLuo, Jianwen-
dc.contributor.authorLiao, Hongen-
dc.date.accessioned2025-11-05T06:55:39Z-
dc.date.available2025-11-05T06:55:39Z-
dc.date.issued2025-
dc.identifier.citationIEEE Reviews in Biomedical Engineering, 2025-
dc.identifier.issn1937-3333-
dc.identifier.urihttp://hdl.handle.net/10722/365365-
dc.description.abstractThe 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.languageeng-
dc.relation.ispartofIEEE Reviews in Biomedical Engineering-
dc.subjectautonomy-
dc.subjectclinical applications-
dc.subjectmedical robotics-
dc.subjectrobot learning-
dc.subjectrobotic ultrasound systems-
dc.subjectUltrasound imaging-
dc.titleToward Clinical Applications of Intelligent Robotic Ultrasound Systems-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/RBME.2025.3610605-
dc.identifier.scopuseid_2-s2.0-105017760165-
dc.identifier.eissn1941-1189-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats