Evidence map›Paper›PMID 38734697›Full record

ArticleNature communications2024

A fully autonomous robotic ultrasound system for thyroid scanning.

Kang Su, Jingwei Liu, Xiaoqi Ren, Yingxiang Huo, Guanglong Du, Wei Zhao, Xueqian Wang, Bin Liang, Di Li, Peter Xiaoping Liu

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
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  4. Personalized scan path planning for robotic ultrasound in head and neck lesions.International journal of computer assisted radiology and surgery · 2026
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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

10 authors.

Kang Su *School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China.ORCID http://orcid.org/0000-0002-3358-161X
Jingwei Liu *School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China.ORCID http://orcid.org/0000-0002-3428-0210
Xiaoqi Ren *School of Future Technology, South China University of Technology, Guangzhou, 511442, China.
Yingxiang Huo *School of Future Technology, South China University of Technology, Guangzhou, 511442, China.ORCID http://orcid.org/0000-0003-1197-5519
Guanglong Du *School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510006, China. csgldu@scut.edu.cn.ORCID http://orcid.org/0000-0001-9425-843X
Wei ZhaoDivision of Vascular and Interventional Radiology, Nanfang Hospital Southern Medical University, Guangzhou, 510515, China.
Xueqian WangTsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China. wang.xq@sz.tsinghua.edu.cn.ORCID http://orcid.org/0000-0003-3542-0593
Bin LiangDepartment of Automation, Tsinghua University, 100854, Beijing, China. bliang@tsinghua.edu.cn.
Di LiSchool of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou, 510641, China.
Peter Xiaoping LiuDepartment of Systems and Computer Engineering, Carleton University, Ottawa, ON, K1S 5B6, Canada. xpliu@sce.carleton.ca.ORCID http://orcid.org/0000-0002-8703-6967

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and the expertise of the radiologist, and the process is physically and cognitively exhausting. In this paper, we report a fully autonomous robotic ultrasound system, which is able to scan thyroid regions without human assistance and identify malignant nod- ules. In this system, human skeleton point recognition, reinforcement learning, and force feedback are used to deal with the difficulties in locating thyroid targets. The orientation of the ultrasound probe is adjusted dynamically via Bayesian optimization. Experimental results on human participants demonstrated that this system can perform high-quality ultrasound scans, close to manual scans obtained by clinicians. Additionally, it has the potential to detect thyroid nodules and provide data on nodule characteristics for American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) calculation.

Indexed as

RoboticsThyroid GlandThyroid NoduleUltrasonographyAdultBayes TheoremFemaleHumansMaleThyroid Neoplasms

Identifiers

PMID38734697
PMCPMC11519952

What OpenQuestion holds

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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.