Qingqing Ling

Southern Medical University

Papers

1

Total Citations

14

H-Index

1

About

Dr. Qingqing Ling is a leading researcher in medical imaging and robotics, with a focus on advancing the accuracy and reliability of CT imaging systems. Their most notable contribution is the development of a knowledge-based self-calibration method for calibration phantoms, specifically designed for robot-based CT imaging systems. This work, published in 2021 and garnering 14 citations, addresses a critical challenge in the field: ensuring precise image reconstruction without manual intervention. By integrating prior knowledge into the calibration process, Dr. Ling's method reduces errors and enhances the practicality of robotic CT systems for clinical and industrial applications. This innovation has significant implications for improving diagnostic imaging and automated surgical guidance. Dr. Ling's research bridges robotics, computer vision, and medical physics, demonstrating a commitment to solving real-world problems through interdisciplinary approaches. Their work is widely recognized for its potential to streamline calibration workflows and improve patient outcomes, making them a rising figure in the field of medical robotics and imaging.

Research Focus

Key Achievements

1
H-Index
1
Papers
14
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Knowledge-based self-calibration method of calibration phantom by and for accurate robot-based CT imaging systems
14 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Southern Medical University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago