AuSoScan: Automatic Scoliosis Assessment by Ultrasound Scanning With Soft Contact Control
Duan, Anqing Liuchen, Wanli Zhou, Peng Song, Dezhen Yang, Chenguang Zheng, Yongping Navarro-Alarcon, David
Duan, Anqing
Liuchen, Wanli
Zhou, Peng
Song, Dezhen
Yang, Chenguang
Zheng, Yongping
Navarro-Alarcon, David
Supervisor
Department
Robotics
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Type
Journal article
Date
2025
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Language
English
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Abstract
In this article, we present AuSoScan, a novel robotic platform that enables automatic scoliosis assessment through ultrasound scanning. Ultrasound imaging has been widely adopted in physical examinations due to its many benefits, such as being radiation-free, cost-effective, and highly portable. However, the scanning procedure is often tedious and labor-intensive, requiring sonographers to perform repetitive manual scanning tasks. With the fast development of robotic technologies in medical and healthcare applications, robotic ultrasound imaging presents a promising solution by combining the strengths of both robotic systems and ultrasonic devices. This has driven the development of AuSoScan, a platform specifically aimed at diagnosing scoliosis, a condition characterized by an abnormal lateral curvature of the spine. The hardware of the research platform consists of an ultrasound probe, a robotic arm, a depth camera, a force/torque sensor, and a workstation. The software architecture of the system comprises an ultrasonic perception model, a control system, and a 3-D spinal image reconstruction program. The control system of AuSoScan is implemented using model predictive control, explicitly accounting for the soft contact between the ultrasound probe and the patient’s back to enable precise force control. The effectiveness of AuSoScan is evaluated by real-world experiments of assessing the scoliosis on a phantom.
Citation
A. Duan et al., "AuSoScan: Automatic Scoliosis Assessment by Ultrasound Scanning With Soft Contact Control," in IEEE/ASME Transactions on Mechatronics, doi: 10.1109/TMECH.2025.3583041
Source
IEEE/ASME Transactions on Mechatronics
Conference
Keywords
Force control, healthcare robotics, image processing, medical robots and systems, robotic ultrasound imaging
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Source
Publisher
IEEE