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About

Yuanwei Li is a leading researcher in medical robotics and autonomous ultrasound imaging, with a focus on developing intelligent systems for breast and lung cancer screening. Their major contributions lie in creating fully autonomous ultrasound scanning robots that eliminate the need for highly skilled sonographers, addressing critical challenges in reproducibility and accessibility. Li's most cited work, "A Flexible and Fully Autonomous Breast Ultrasound Scanning System" (2022, 37 citations), introduces a robotic system that autonomously controls probe contact force to ensure high-quality imaging. This is complemented by "Fully Automatic Dual-Probe Lung Ultrasound Scanning Robot for Screening Triage" (2022, 25 citations), a rapid, noninvasive tool for COVID-19 diagnosis that reduces operator-dependent variability. Li also pioneered "Automatic Generation of Autonomous Ultrasound Scanning Trajectory Based on 3-D Point Cloud" (2022, 23 citations), enabling robots to adapt to diverse human anatomies, and "Autonomous Trajectory Planning for Ultrasound-Guided Real-Time Tracking of Suspicious Breast Tumor Targets" (2023, 15 citations), which enhances precision in tumor localization and biopsy. Their recent work, "DHDP-SLAM: Dynamic Hierarchical Dirichlet Process based data association for semantic SLAM" (2024, 3 citations), extends into semantic mapping for robotic navigation. With over 100 citations across their key papers, Li’s innovations are paving the way for scalable, autonomous medical imaging, promising to democratize access to high-quality diagnostics.