Beyond hospital reach: Autonomous lightweight ultrasound robot for liver sonography

These authors contributed equally to this work Abstract: Liver disease is a major global health burden. While ultrasound is the first-line diagnostic tool, liver sonography requires locating multiple non-continuous planes from positions where target structures are often not visible, for biometric assessment and lesion detection, requiring significant expertise. However, expert sonographers are severely scarce in resource-limited regions. Here, we develop an autonomous lightweight ultrasound robot comprising an AI agent that integrates multi-modal perception with memory attention for localization of unseen target structures, and a 588-gram 6-degrees-of-freedom cable-driven robot. By mounting on the abdomen, the system enhances robustness against motion. Our robot can autonomously acquire expert-level standard liver ultrasound planes and detect pathology in patients, including two from Xining, a 2261-meter-altitude city with limited medical resources. Our system performs effectively on rapid-motion individuals and in wilderness environments. This work represents the first demonstration of autonomous sonography across multiple challenging scenarios, potentially transforming access to expert-level diagnostics in underserved regions. One-Sentence Summary: The lightweight robot enables autonomous liver non-continuous standard plane sonography across multiple scenarios. Main Text: INTRODUCTION Liver disease represents a major global health burden, accounting for over two million deaths annually--approximately 4% of worldwide mortality. Cirrhosis and hepatocellular carcinoma constitute the predominant causes of liver-related fatalities. Meanwhile, parasitic infections pose additional challenges, particularly in resource-limited settings ( 1-3).