Image-Guided Navigation of a Robotic Ultrasound Probe for Autonomous Spinal Sonography Using a Shadow-aware Dual-Agent Framework

Li，Keyu1; Xu，Yangxin2; Wang，Jian3; Ni，Dong3; Liu，Li2; Meng，Max Q.H.4

2021

10.1109/TMRB.2021.3127015

IEEE Transactions on Medical Robotics and Bionics   影响因子和分区

2576-3202

2576-3202

Ultrasound (US) imaging is commonly used to assist in the diagnosis and interventions of spine diseases, while the standardized US acquisitions performed by manually operating the probe require substantial experience and training of sonographers. In this work, we propose a novel dual-agent framework that integrates a reinforcement learning (RL) agent and a deep learning (DL) agent to jointly determine the movement of the US probe based on the real-time US images, in order to mimic the decision-making process of an expert sonographer to achieve autonomous standard view acquisitions in spinal sonography. Moreover, inspired by the nature of US propagation and the characteristics of the spinal anatomy, we introduce a view-specific acoustic shadow reward to utilize the shadow information to implicitly guide the navigation of the probe toward different standard views of the spine. Our method is validated in both quantitative and qualitative experiments in a simulation environment built with US data acquired from 17 volunteers. The average navigation accuracy toward different standard views achieves 5.18mm/5.25∘ and 12.87mm/17.49∘ in the intra-and inter-subject settings, respectively. The results demonstrate that our method can effectively interpret the US images and navigate the probe to acquire multiple standard views of the spine.

Imaging Medical robotic system Navigation Probes Robot decision-making Robotic ultrasound Robots Spine Standards Three-dimensional displays Ultrasound image analysis.

EI

英语

其他

20214711211300

Deep learning ; Diagnosis ; Medical imaging ; Navigation ; Probes ; Reinforcement learning ; Robotics ; Robots ; Three dimensional displays ; Ultrasonic imaging

Biomedical Engineering:461.1 ; Ergonomics and Human Factors Engineering:461.4 ; Medicine and Pharmacology:461.6 ; Computer Peripheral Equipment:722.2 ; Artificial Intelligence:723.4 ; Robotics:731.5 ; Imaging Techniques:746 ; Management:912.2

2-s2.0-85119426867

Scopus

1.Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China. (e-mail: kyli@link.cuhk.edu.hk)
2.Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, China.
3.School of Biomedical Engineering, Shenzhen University, Shenzhen, China.
4.Department of Electronic and Electrical Engineering of the Southern University of Science and Technology in Shenzhen, China, on leave from the Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong, and also with the Shenzhen Research Institute of the Chinese University of Hong Kong in Shenzhen, China.

Li，Keyu,Xu，Yangxin,Wang，Jian,et al. Image-Guided Navigation of a Robotic Ultrasound Probe for Autonomous Spinal Sonography Using a Shadow-aware Dual-Agent Framework[J]. IEEE Transactions on Medical Robotics and Bionics,2021,4(1):130-144.

Li，Keyu,Xu，Yangxin,Wang，Jian,Ni，Dong,Liu，Li,&Meng，Max Q.H..(2021).Image-Guided Navigation of a Robotic Ultrasound Probe for Autonomous Spinal Sonography Using a Shadow-aware Dual-Agent Framework.IEEE Transactions on Medical Robotics and Bionics,4(1),130-144.

Li，Keyu,et al."Image-Guided Navigation of a Robotic Ultrasound Probe for Autonomous Spinal Sonography Using a Shadow-aware Dual-Agent Framework".IEEE Transactions on Medical Robotics and Bionics 4.1(2021):130-144.