Autonomous robotic ultrasound scanning system: a key to enhancing image analysis reproducibility and observer...

This study aims to develop an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline, comparing its reproducibility and observer consistency in image analysis with physicians of varying levels of expertise.

An auto-RUSS was engineered using a 7-degree-of-freedom robotic arm, with real-time regulation based on force control and ultrasound visual servoing. Two phantoms were employed for the human-machine comparative experiment, involving three groups: auto-RUSS, non-expert (4 junior physicians), and expert (4 senior physicians). This setup enabled comprehensive assessment of reproducibility in contact force, image acquisition, image measurement and AI-assisted classification. Radiological feature variability was measured using the coefficient of variation (COV), while performance and reproducibility assessments utilized mean and standard deviation (SD).

The auto-RUSS had the potential to reduce operator-dependent variability in ultrasound examinations, offering enhanced repeatability and consistency across multiple dimensions including probe contact force, images acquisition, image measurement, and diagnostic model performance.

In this paper, an autonomous robotic ultrasound scanning system (auto-RUSS) pipeline was proposed. Through comprehensive human-machine comparison experiments, the auto-RUSS was shown to effectively improve the reproducibility of ultrasound images and minimize human-induced variability.