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

arXiv cs.CV / 4/2/2026

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Key Points

  • The paper introduces HiCT, a two-stage framework to reconstruct high-precision 3D dental CBCT from a single low-dose panoramic X-ray, aiming to reduce the radiation dose and cost barriers of conventional CBCT.
  • HiCT first uses a video diffusion model to generate geometrically consistent multi-view projections from one panoramic image, addressing geometric inconsistencies that hinder single-view approaches.
  • It then performs CBCT reconstruction from those projections using a ray-based dynamic attention network combined with an X-ray sampling strategy to improve fidelity.
  • The authors also release/describe XCT, a large dataset built from public CBCT data plus 500 paired PX-CBCT cases, enabling more effective training and evaluation.
  • Experiments on the proposed pipeline report state-of-the-art results with reconstructions claimed to be accurate and geometrically consistent enough for clinical use.

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.