English

HICT: High-precision 3D CBCT reconstruction from a single X-ray

Computer Vision and Pattern Recognition 2026-04-02 v1

Abstract

Accurate 3D dental imaging is vital for diagnosis and treatment planning, yet CBCT's high radiation dose and cost limit its accessibility. Reconstructing 3D volumes from a single low-dose panoramic X-ray is a promising alternative but remains challenging due to geometric inconsistencies and limited accuracy. We propose HiCT, a two-stage framework that first generates geometrically consistent multi-view projections from a single panoramic image using a video diffusion model, and then reconstructs high-fidelity CBCT from the projections using a ray-based dynamic attention network and an X-ray sampling strategy. To support this, we built XCT, a large-scale dataset combining public CBCT data with 500 paired PX-CBCT cases. Extensive experiments show that HiCT achieves state-of-the-art performance, delivering accurate and geometrically consistent reconstructions for clinical use.

Cite

@article{arxiv.2604.00792,
  title  = {HICT: High-precision 3D CBCT reconstruction from a single X-ray},
  author = {Wen Ma and Jiaxiang Liu and Zikai Xiao and Ziyang Wang and Feng Yang and Zuozhu Liu},
  journal= {arXiv preprint arXiv:2604.00792},
  year   = {2026}
}
R2 v1 2026-07-01T11:48:05.730Z