Related Experiment Video
Updated: Jul 6, 2026
A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Feasibility and preliminary validation of an autonomous robotic ultrasound system for thyroid nodule screening: a
Jiakang Zhou1, Shaozhang Xie2, Wei Wang3
1School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, 710072, China.
Purpose:
Thyroid nodules are highly prevalent in the general population, yet large-scale ultrasound screening is limited by its reliance on experienced sonographers. Autonomous robotic ultrasound systems have the potential to enable standardized thyroid screening with reduced operator dependency.
Methods:
In this pilot prospective study, a fully autonomous robotic ultrasound system was evaluated for thyroid nodule screening in a clinical setting. Twenty-one consecutive participants underwent both autonomous robotic ultrasound and standard operator-performed ultrasound examinations in a randomized order. The primary outcome was participant-level thyroid nodule detection rate compared with operator-performed ultrasound. Secondary outcomes included feasibility, thyroid gland coverage, and participant-reported comfort.
Results:
Autonomous robotic ultrasound was successfully completed without human intervention in 20 of 21 participants (95.2%). Thyroid nodules were identified on operator-performed ultrasound in nine participants, of whom eight were correctly detected by the autonomous system, corresponding to a participant-level detection rate of 88.9%. Complete coverage of the left lobe, right lobe, and isthmus was achieved in 100%, 95%, and 80% of participants, respectively. Participant-reported comfort was neutral to positive, with a median Likert score of 3 (interquartile range, 3-4).
Conclusion:
This pilot study demonstrated the feasibility of fully autonomous robotic ultrasound for standardized thyroid nodule screening. The system achieved high completion rates and acceptable screening performance in a controlled clinical setting, supporting further validation in larger and more diverse populations.
