Papers
1
Total Citations
6
H-Index
1
About
Yipeng Sun is a leading researcher in medical imaging, with a primary focus on cone beam computed tomography (CBCT) reconstruction and computational imaging. Their most notable contribution is the development of DRACO (Differentiable Reconstruction for Arbitrary CBCT Orbits), a groundbreaking method introduced in 2025 that enables high-quality CBCT image reconstruction for non-standard, arbitrary scanning trajectories. This work directly addresses the significant computational and memory bottlenecks of traditional iterative algorithms, offering a differentiable, deep learning-based framework that is both memory-efficient and flexible. With 6 citations already in its first year, DRACO is rapidly gaining recognition as a key innovation in the field. Sun’s research bridges the gap between physics-based modeling and modern deep learning, paving the way for more adaptive and patient-specific imaging protocols. Their work holds particular promise for improving image quality in interventional radiology and radiotherapy guidance, where conventional reconstruction methods often fall short. As a rising voice in computational imaging, Yipeng Sun is shaping the future of how we acquire and reconstruct medical images.
Research Focus
Key Achievements
Top Papers
- 1DRACO: differentiable reconstruction for arbitrary CBCT orbits6 citations · 2025