Yanjun Guo

Papers

Total Citations

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About

Yanjun Guo is a leading researcher in medical robotics and intelligent surgical systems, with a focus on developing autonomous technologies for high-precision interventions. Their work bridges computer vision and robotic navigation, particularly in breast ultrasound and cranio-maxillofacial surgery. Guo’s most cited paper (2021, 46 citations) introduces an expanded U-Net architecture for fully automatic, real-time segmentation and recognition of breast ultrasound images, enabling a robotic system to assist in interventions with enhanced accuracy and speed. This contribution is pivotal for advancing autonomous diagnostic and therapeutic tools in oncology. Earlier, Guo developed a novel navigation system for a cranio-maxillofacial surgical robot (2018, 9 citations), addressing the high-risk, high-accuracy demands of procedures like skull base lesion biopsy and radiofrequency thermocoagulation. By integrating modelling and experimental validation, this work demonstrated a versatile robotic platform capable of assisting surgeons in complex anatomical regions. Guo’s research exemplifies the synergy of deep learning and robotics, offering tangible solutions for minimally invasive surgery. Their contributions are shaping the next generation of intelligent surgical assistants, with potential to improve patient outcomes and procedural safety in challenging clinical scenarios.