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These artifacts arise from the polychromatic nature of X\u2010rays and are not properly addressed by conventional monochromatic reconstruction algorithms. While recent neural representation\u2010based methods offer improved reconstruction quality, they are computationally expensive and often impractical for deployment. We propose a novel physics\u2010inspired, self\u2010calibrating metal artifact reduction method that efficiently reconstructs 3D CBCT volumes while correcting beam hardening artifacts. Our method integrates a polychromatic X\u2010ray projection model, material\u2010dependent 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\u2010ray spectral characteristics jointly during training. We further introduce a high\u2010fidelity synthetic CBCT dataset generation pipeline validated on Monte\u2010Carlo x\u2010ray simulation toolbox and release new datasets with severe metal\u2010induced artifacts to support the community. This is the first splat\u2010based method for reducing beam hardening in CBCT. Extensive experiments on both synthetic and real\u2010world datasets demonstrate that our method outperforms state\u2010of\u2010the\u2010art approaches in artifact suppression and reconstruction accuracy.<\/jats:p>","DOI":"10.1111\/cgf.70339","type":"journal-article","created":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T13:27:24Z","timestamp":1774618044000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Splat\u2010based Metal Artifact Reduction in Cone\u2010Beam CT via Polychromatic Modeling"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2352-3889","authenticated-orcid":false,"given":"Kiseok","family":"Choi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1268-3104","authenticated-orcid":false,"given":"Inchul","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2800-5105","authenticated-orcid":false,"given":"Jaemin","family":"Cho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9399-4232","authenticated-orcid":false,"given":"Hyeongjun","family":"Cho","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5078-4005","authenticated-orcid":false,"given":"Min H.","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,3,27]]},"reference":[{"issue":"2","key":"e_1_2_12_2_2","doi-asserted-by":"crossref","first-page":"915","DOI":"10.1118\/1.3528204","article-title":"The lung image database consortium (lidc) and image database resource initiative (idri): a completed reference database of lung nodules on ct scans","volume":"38","author":"Armato S. 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