ArticleIEEE robotics and automation letters2025
A-SEE2.0: Active-Sensing End-Effector for Robotic Ultrasound Systems with Dense Contact Surface Perception Enabled Probe Orientation Adjustment.
Article in IEEE robotics and automation letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Intensity Variance-Guided Automated Robotic Optical Coherence Tomography System for Ophthalmic Applications.Journal of biophotonics · 2026Article
- Technical challenges in autonomous robotic ultrasound examinations: perception, planning, and control.Journal of robotic surgery · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Conventional freehand ultrasound (US) imaging is highly dependent on the skill of the operator, leading to inconsistent results and increased physical burden on sonographers. Robotic Ultrasound Systems (RUSS) aim to address these limitations by providing standardized and automated imaging solutions, especially in environments with limited access to skilled operators. This paper presents the development of a RUSS system that employs a novel end-effector, A-SEE2.0, which uses dual RGB-D depth cameras to maintain the US probe normal to the skin surface, a default starting configuration for anatomical landmarks identification. Our RUSS integrates RGB-D camera data with robotic control algorithms to maintain orthogonal probe alignment on uneven surfaces without preoperative data. Validation tests using a phantom model show that the system achieves robust normal positioning accuracy. A-SEE2.0 demonstrates 2.47 ± 1.25 degrees normal positioning error on a flat surface and 12.19 ± 5.81 degrees error on a mannequin surface. This work highlights the clinical potential of A-SEE2.0 by demonstrating that, during in-vivo forearm ultrasound examinations, it achieves image quality comparable to manual scanning by a human sonographer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.