ArticleJournal of applied clinical medical physics2016
An energy minimization method for the correction of cupping artifacts in cone-beam CT.
Article in Journal of applied clinical medical physics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- CBCT-to-CT synthesis using a hybrid U-Net diffusion model based on transformers and information bottleneck theory.Scientific reports · 2025Article
- CBCT-Based synthetic CT image generation using conditional denoising diffusion probabilistic model.Medical physics · 2024Article
- Multitask 3D CBCT-to-CT translation and organs-at-risk segmentation using physics-based data augmentation.Medical physics · 2021Article
- Synthetic CT generation from CBCT images via deep learning.Medical physics · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to reduce cupping artifacts and improve quantitative accuracy of the images in cone-beam CT (CBCT). An energy minimization method (EMM) is proposed to reduce cupping artifacts in reconstructed image of the CBCT. The cupping artifacts are iteratively optimized by using efficient matrix computations, which are verified to be numerically stable by matrix analysis. Moreover, the energy in our formulation is convex in each of its variables, which brings the robustness of the proposed energy minimization algorithm. The cupping artifacts are estimated as a result of minimizing this energy. The results indicate that proposed algorithm is effective for reducing the cupping artifacts and preserving the quality of the reconstructed image. The proposed method focuses on the reconstructed image without requiring any additional physical equipment; it is easily implemented and provides cupping correction using a single scan acquisition. The experimental results demonstrate that this method can successfully reduce the magnitude of cupping artifacts. The correction algorithm reported here may improve the uniformity of the reconstructed images, thus assisting the development of perfect volume visualization and threshold-based visualization techniques for reconstructed images.
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Registered trials
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