Metraipolis › archive › dc_fb4624efc9aa

Splat-based Metal Artifact Reduction in Cone-Beam CT via Polychromatic Modeling — arXiv:2608.13159

Source: arXiv (en)
Original: https://arxiv.org/abs/2608.13159
License (as archived): CC0-1.0
Archived: 2026-10-19T04:55:49.263Z
SHA-256 of the archived text: 8b24aa829b9a2b81dc0842b29b57e3e21a9709722b06cef65844b8e3783d7eb2
Stable URL of this page: https://metraipolis.com/documento/dc_fb4624efc9aa

How to cite

Splat-based Metal Artifact Reduction in Cone-Beam CT via Polychromatic Modeling — arXiv:2608.13159 — arXiv (en), https://arxiv.org/abs/2608.13159 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_fb4624efc9aa (Metraipolis archive dc_fb4624efc9aa, sha256 8b24aa829b9a2b81dc0842b29b57e3e21a9709722b06cef65844b8e3783d7eb2)

BibTeX

@misc{dcfb4624efc9aa,
  title = {Splat-based Metal Artifact Reduction in Cone-Beam CT via Polychromatic Modeling — arXiv:2608.13159},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2608.13159},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_fb4624efc9aa; sha256 8b24aa829b9a2b81dc0842b29b57e3e21a9709722b06cef65844b8e3783d7eb2},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2608.13159. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Cone-beam computed tomography (CBCT) enables volumetric reconstruction from X-ray projections, but suffers from severe artifacts--especially beam hardening--when imaging materials with high attenuation such as metals. These artifacts arise from the polychromatic nature of X-rays and are not properly addressed by conventional monochromatic reconstruction algorithms. While recent neural representation-based methods offer improved reconstruction quality, they are computationally expensive and often impractical for deployment. We propose a novel physics-inspired, self-calibrating metal artifact reduction method that efficiently reconstructs 3D CBCT volumes while correcting beam hardening artifacts. Our method integrates a polychromatic X-ray projection model, material-dependent attenuation profiles, and system response modeling into a Gaussian Splatting framework. Unlike prior work, we eliminate the need for manual metal masks or strong prior assumptions, and we optimize both reconstruction parameters and X-ray spectral characteristics jointly during training. We further introduce a high-fidelity synthetic CBCT dataset generation pipeline validated on Monte-Carlo x-ray simulation toolbox and release new datasets with severe metal-induced artifacts to support the community. This is the first splat-based method for reducing beam hardening in CBCT. Extensive experiments on both synthetic and real-world datasets demonstrate that our method outperforms state-of-the-art approaches in artifact suppression and reconstruction accuracy.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-08-14 in cs.CV).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV) ; Graphics (cs.GR).
Pagina del lavoro: https://arxiv.org/abs/2608.13159 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-19T04:46:30.160Z dalla pagina https://arxiv.org/catchup/cs.CV/2026-08-14?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).