Papers
15
Total Citations
570
H-Index
10
About
Qinghua Huang is a leading researcher at the intersection of medical robotics, ultrasound imaging, and artificial intelligence, whose work is transforming how clinicians acquire and interpret diagnostic images. His research centers on developing autonomous and robot-assisted ultrasound scanning systems capable of generating high-quality three-dimensional reconstructions without relying on operator expertise. His landmark 2018 paper on robotic arm-based automatic ultrasound scanning for 3D imaging has garnered over 220 citations, establishing foundational principles for skin-surface-guided probe navigation using depth cameras. A companion study that same year on fully automatic 3D ultrasound further cemented his influence, attracting more than 100 citations. Huang has extended these innovations to clinically critical applications, including spine assessment as a radiation-free alternative to X-ray, carotid artery imaging for cardiovascular risk prediction, and automated thyroid screening. His 2023 review of robot-assisted medical ultrasound systems provides the field with a comprehensive technological and clinical reference. More recently, he has incorporated machine learning—including graph neural networks for movement classification—to support robotic rehabilitation. Across more than a decade of sustained output, Huang's cumulative citation record reflects a researcher who is actively shaping the future of intelligent, reproducible, and accessible medical imaging.
Research Focus
Key Achievements
Top Papers
- 1Robotic Arm Based Automatic Ultrasound Scanning for Three-Dimensional Imaging223 citations · 2018
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- 6Robot-Assisted Autonomous Ultrasound Imaging for Carotid Artery25 citations · 2024
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