Hongliang Qi

Papers

1

Total Citations

14

H-Index

1

About

Hongliang Qi is a researcher specializing in medical imaging and robotic systems, with a focus on improving the accuracy and reliability of computed tomography (CT) imaging. His key research areas include CT imaging calibration, robot-assisted imaging systems, and phantom-based quality assurance. Qi’s most notable contribution is the development of a knowledge-based self-calibration method for calibration phantoms, which enhances the precision of robot-based CT imaging systems. This work, published in 2021, has garnered 14 citations, reflecting its relevance in advancing medical imaging technology. By addressing the challenges of phantom calibration, Qi’s research enables more accurate imaging for clinical and industrial applications, reducing errors in robot-guided procedures. His achievements demonstrate a commitment to bridging robotics and imaging, offering practical solutions for high-stakes environments like surgery and diagnostics. For students and researchers, Qi’s work exemplifies how targeted innovations in calibration can significantly impact the reliability of complex imaging systems.

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

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago