Evidence map›Paper›PMID 40995401›Full record

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.

Yernar Zhetpissov, Xihan Ma, Kehan Yang, Haichong K Zhang

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yernar ZhetpissovDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Xihan MaDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Kehan YangDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA 01609 USA.
Haichong K ZhangDepartment of Robotics Engineering, Worcester Polytechnic Institute, Worcester, MA 01609 USA.

Funding

Physician Assistance Technology in Image-guided Robotic Intervention of ProstateR01EB030539 · NIBIB · BRIGHAM AND WOMEN'S HOSPITAL · PI HATA, NOBUHIKO, ZHANG, HAICHONG · 2021 to 2024
$2.7M
Automatic Wide-Field Optical Coherence Tomography for Assessment of Transplant Kidney ViabilityR01DK133717 · NIDDK · UNIVERSITY OF MASSACHUSETTS AMHERST · PI POTTER, STEVEN, TANG, QINGGONG · 2022 to 2025
$2.5M
Robotic Lung Ultrasound for Triage of COVID-19 Patients in a Resource-Limited EnvironmentDP5OD028162 · OD · WORCESTER POLYTECHNIC INSTITUTE · PI ZHANG, HAICHONG · 2019 to 2023
$2.3M
NIBIB NIH HHS R01 EB030539NIDDK NIH HHS R01 DK133717NIH HHS DP5 OD028162
6 · The paper itself

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.

Indexed as

Computer vision for medical roboticsmedical robots and systemsrobotics and automation in life sciencessensor-based control

Identifiers

PMID40995401
PMCPMC12456402

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Registered trials

None linked

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.