ArticleVisual computing for industry, biomedicine, and art2022
A projection-domain iterative algorithm for metal artifact reduction by minimizing the total-variation norm and the negative-pixel energy.
Article in Visual computing for industry, biomedicine, and art, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Application of streak metal artifact reduction technique in cone-beam computed tomography guided percutaneous transthoracic needle biopsy.World journal of radiology · 2026Article
- Application of digital radiography and digital tomosynthesis in the postoperative evaluation of hip arthroplasty.Radiologie (Heidelberg, Germany) · 2025Article
- AAPM CT metal artifact reduction grand challenge.Medical physics · 2025Article
- Morphing from the TV-Norm to theBiomedical journal of scientific & technical research · 2024Article
- Neural network guided sinogram-domain iterative algorithm for artifact reduction.Medical physics · 2023Article
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1 author.
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Abstract
Metal objects in X-ray computed tomography can cause severe artifacts. The state-of-the-art metal artifact reduction methods are in the sinogram inpainting category and are iterative methods. This paper proposes a projection-domain algorithm to reduce the metal artifacts. In this algorithm, the unknowns are the metal-affected projections, while the objective function is set up in the image domain. The data fidelity term is not utilized in the objective function. The objective function of the proposed algorithm consists of two terms: the total variation of the metal-removed image and the energy of the negative-valued pixels in the image. After the metal-affected projections are modified, the final image is reconstructed via the filtered backprojection algorithm. The feasibility of the proposed algorithm has been verified by real experimental data.
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