Xiaoman Duan
Papers
1
Total Citations
14
H-Index
1
About
Xiaoman Duan is a leading researcher in medical imaging and robotic systems, with a primary focus on enhancing the accuracy and reliability of computed tomography (CT) imaging. Her most notable contribution is the development of a knowledge-based self-calibration method for calibration phantoms, designed specifically for robot-based CT imaging systems. This innovative approach, detailed in her 2021 paper, addresses critical challenges in image reconstruction by enabling autonomous calibration without external references, significantly improving spatial precision in clinical and industrial applications. With 14 citations, this work has garnered attention for its practical impact on reducing artifacts and streamlining calibration workflows. Duan’s research bridges robotics and medical physics, offering scalable solutions for high-fidelity imaging in complex environments. Her achievements underscore a commitment to advancing non-invasive diagnostic tools, making her a rising authority in the integration of intelligent systems with medical imaging technology.
Research Focus
Key Achievements
Top Papers
- 1