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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.14315 |
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| _version_ | 1866910023326629888 |
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| author | Rautio, Siiri Meaney, Alexander Latva-Äijö, Salla-Maaria Agrawal, Harshit Brix, Mikael Jayakody, Dinidu Siltanen, Samuli |
| author_facet | Rautio, Siiri Meaney, Alexander Latva-Äijö, Salla-Maaria Agrawal, Harshit Brix, Mikael Jayakody, Dinidu Siltanen, Samuli |
| contents | Metal objects pose a significant challenge in cone-beam computed tomography, as their strong and energy-dependent X-ray attenuation leads to inconsistent projections and severe streaking and shading artifacts in reconstructed images. These artifacts degrade image quality and limit the reliability of subsequent medical analysis. We propose a projection-domain metal artifact reduction method based on analytical metal segmentation in the three-dimensional sinogram using the three-dimensional Dual-Tree Complex Wavelet Transform, where directional wavelet coefficients are exploited to extract the wavefront set and singular support of metal structures. The resulting segmentation enables projection-domain inpainting and artifact-reduced reconstruction by combining metal-free and metal-only reconstructions. The proposed approach is evaluated on both simulated and clinical cone-beam computed tomography data and consistently reduces metal artifacts compared to conventional image-domain hard-thresholding methods. The results demonstrate improved visual quality and robustness in clinically realistic scenarios, highlighting the potential of analytically grounded, non-learned projection-domain segmentation for metal artifact reduction. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_14315 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Complex Wavelet-Based Sinogram Segmentation for Metal Artifact Reduction in Cone-Beam CT Rautio, Siiri Meaney, Alexander Latva-Äijö, Salla-Maaria Agrawal, Harshit Brix, Mikael Jayakody, Dinidu Siltanen, Samuli Medical Physics Numerical Analysis Metal objects pose a significant challenge in cone-beam computed tomography, as their strong and energy-dependent X-ray attenuation leads to inconsistent projections and severe streaking and shading artifacts in reconstructed images. These artifacts degrade image quality and limit the reliability of subsequent medical analysis. We propose a projection-domain metal artifact reduction method based on analytical metal segmentation in the three-dimensional sinogram using the three-dimensional Dual-Tree Complex Wavelet Transform, where directional wavelet coefficients are exploited to extract the wavefront set and singular support of metal structures. The resulting segmentation enables projection-domain inpainting and artifact-reduced reconstruction by combining metal-free and metal-only reconstructions. The proposed approach is evaluated on both simulated and clinical cone-beam computed tomography data and consistently reduces metal artifacts compared to conventional image-domain hard-thresholding methods. The results demonstrate improved visual quality and robustness in clinically realistic scenarios, highlighting the potential of analytically grounded, non-learned projection-domain segmentation for metal artifact reduction. |
| title | Complex Wavelet-Based Sinogram Segmentation for Metal Artifact Reduction in Cone-Beam CT |
| topic | Medical Physics Numerical Analysis |
| url | https://arxiv.org/abs/2602.14315 |