Dengwang Li

About

Dengwang Li is a leading researcher in medical image analysis and radiation therapy, with a focus on developing intelligent systems for motion management in cancer treatment. His key research areas include ultrasound imaging, machine learning, and computer vision for real-time motion tracking during abdominal radiation therapy. Li’s major contributions center on creating deep learning frameworks that enhance the accuracy and speed of intra-fraction respiratory motion tracking. Notably, his work on an attention-aware fully convolutional neural network integrated with convolutional long short-term memory networks achieved 32 citations, demonstrating its impact on ultrasound-based motion tracking. He also pioneered a 2D ultrasound imaging system using machine learning to overcome previous limitations in tracking abdominal motions under free-breathing conditions, a breakthrough that garnered 26 citations. Li’s innovative use of robotic-arm-mounted ultrasound systems, combined with advanced neural networks, has significantly improved the feasibility of real-time motion management in radiation therapy, offering high soft tissue contrast and real-time capability without ionizing radiation. His achievements position him as a key contributor to safer, more precise cancer treatments, inspiring further research in medical imaging and AI-driven clinical applications.

Research Focus

Key Achievements

Top Papers

1. 1
   Attention‐aware fully convolutional neural network with convolutional long short‐term memory network for ultrasound‐based motion tracking

   32 citations · 2019
2. 2
   2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning

   26 citations · 2019

Key Collaborators

Contact & Links