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

Wen Ma, Jiaxiang Liu, Zikai Xiao, Ziyang Wang, Feng Yang +1 more
4/1/2026
cs.CV

No confident code implementation found for this paper.

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{ma2026hict,
  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},
  year   = {2026},
  eprint = {2604.00792},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2604.00792v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2604.00792.svg)](https://codeofpaper.com/paper/2604.00792)

Discussion