Danhua Liu
Papers
1
Total Citations
32
H-Index
1
About
Danhua Liu is a leading researcher in medical image analysis and radiation therapy, with a primary focus on developing advanced deep learning techniques for motion management in cancer treatment. Her most cited work introduces an attention-aware fully convolutional neural network integrated with convolutional long short-term memory networks for ultrasound-based motion tracking, a critical innovation for real-time tumor localization during radiotherapy. This approach leverages the high soft tissue contrast and real-time capabilities of robotic-arm-mounted ultrasound systems, offering a non-ionizing, cost-effective alternative for motion management. With over 30 citations, this paper highlights her expertise in combining attention mechanisms with recurrent architectures to enhance tracking accuracy in dynamic clinical settings. Liu’s contributions are pivotal in advancing LINAC-compatible imaging solutions, directly impacting the precision and safety of radiation therapy. Her work bridges computer vision and clinical oncology, demonstrating how deep learning can address practical challenges in cancer care. As a researcher, she continues to push boundaries in ultrasound-guided interventions, making her a key figure in the intersection of artificial intelligence and medical physics.
Research Focus
Key Achievements
Top Papers
- 1