ArticleIEEE robotics and automation letters2022
A-SEE: Active-Sensing End-effector Enabled Probe Self-Normal-Positioning for Robotic Ultrasound Imaging Applications.
Article in IEEE robotics and automation letters, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Technical challenges in autonomous robotic ultrasound examinations: perception, planning, and control.Journal of robotic surgery · 2026Review
- Autonomous path planning for intercostal robotic ultrasound imaging using reinforcement learning.Scientific reports · 2026Article
- Fully automated robotic ultrasound gallbladder imaging with subcostal scanning.Scientific reports · 2025Article
- A-SEE2.0: Active-Sensing End-Effector for Robotic Ultrasound Systems with Dense Contact Surface Perception Enabled Probe Orientation Adjustment.IEEE robotics and automation letters · 2025Article
- Intraoperative laparoscopic photoacoustic image guidance system in the da Vinci surgical system.Biomedical optics express · 2023Article
- Cross-Modality Registration using Bone Surface Pointcloud for Robotic Ultrasound-Guided Spine Surgery.Journal of medical robotics researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Conventional manual ultrasound (US) imaging is a physically demanding procedure for sonographers. A robotic US system (RUSS) has the potential to overcome this limitation by automating and standardizing the imaging procedure. It also extends ultrasound accessibility in resource-limited environments with the shortage of human operators by enabling remote diagnosis. During imaging, keeping the US probe normal to the skin surface largely benefits the US image quality. However, an autonomous, real-time, low-cost method to align the probe towards the direction orthogonal to the skin surface without pre-operative information is absent in RUSS. We propose a novel end-effector design to achieve self-normal-positioning of the US probe. The end-effector embeds four laser distance sensors to estimate the desired rotation towards the normal direction. We then integrate the proposed end-effector with a RUSS system which allows the probe to be automatically and dynamically kept to normal direction during US imaging. We evaluated the normal positioning accuracy and the US image quality using a flat surface phantom, an upper torso mannequin, and a lung ultrasound phantom. Results show that the normal positioning accuracy is 4.17 ± 2.24 degrees on the flat surface and 14.67 ± 8.46 degrees on the mannequin. The quality of the RUSS collected US images from the lung ultrasound phantom was equivalent to that of the manually collected ones.
Indexed as
Identifiers
What OpenQuestion holds
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.