Hengjie Liu

University of California, Los Angeles

Papers

2

Total Citations

11

H-Index

2

About

Hengjie Liu is a researcher at the forefront of medical image analysis and radiation oncology, specializing in real-time tumor tracking for stereotactic body radiation therapy (SBRT). His work addresses the critical challenge of accurately localizing tumors that are poorly visible on X-ray images, particularly when traditional fiducial markers are absent. Liu’s major contributions include the development of a zero-shot deep learning framework, "Deep match," which enables robust, fiducial-free respiratory motion tracking—a breakthrough that eliminates the need for invasive marker implantation. This work has garnered early attention, with 8 citations since its 2024 publication, signaling its potential to transform clinical workflows. Additionally, his research on robust localization of poorly visible tumors has earned 3 citations, further underscoring his impact in enhancing treatment precision. Liu’s achievements are notable for their practical focus: by improving motion tracking accuracy without requiring additional hardware or patient preparation, his methods promise to make SBRT safer and more accessible. As a rising voice in medical physics, Liu is shaping the next generation of adaptive radiotherapy.

Research Focus

Key Achievements

2
H-Index
2
Papers
11
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking
8 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of California, Los Angeles

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago