Guang‐Biao Chen

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About

Guang-Biao Chen is a leading researcher in medical image processing and robot-assisted surgical systems, with a focused expertise on improving early cancer diagnosis and minimally invasive interventions. His work primarily addresses the critical challenges in lung cancer detection and treatment, where he has developed innovative methods for lung nodule pre-diagnosis using chest CT images, as well as advanced lesion positioning techniques for CT-guided surgical robotic systems. Chen’s notable contributions include establishing lesion and needle positioning methods that ensure puncture accuracy—a key technical foundation for robot-assisted percutaneous lung procedures. His experimental studies on optimum puncture patterns for needle insertion into hyperelastic materials have further refined insertion parameters to reduce patient pain and improve procedural reach. With his most-cited papers accumulating 11, 9, and 8 citations respectively, Chen’s research is gaining traction in the surgical robotics and medical imaging communities. His work on insertion path planning and robotic system integration represents a significant step toward reliable, automated assistance in early-stage cancer diagnosis and treatment, positioning him as a promising contributor to the future of precision oncology and minimally invasive surgery.