ArticleMedical physics2026
Look-up table correction for beam hardening-induced signal of clinical dark-field chest radiographs.
Article in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Beam-hardening correction in clinical x-ray dark-field chest radiography using deep-learning-based bone segmentation.Medical physics · 2026Article
- Look-up table correction for beam hardening-induced signal of clinical dark-field chest radiographs.Medical physics · 2026Article
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Authors and funding
7 authors.
Funding
Abstract
backgroundThe microstructure of material at a PURPOSE: The objective of this study is to develop a fast, simple, and robust method to correct dark-field signals and bony structures present due to beam hardening on dark-field chest radiographs of study participants.
methodsThe method is based on calibration measurements and image processing. BH by bones and soft tissue is modeled by aluminum and water, respectively, which have no microstructure and thus only generate an artificial dark-field signal. Look-up tables were then created for both. By using a weighted mean of these, forming a single LUT, and using the attenuation images, the artificial dark-field signal and thus the bone structures present are reduced for study participants.
resultsIt was found that applying a correction using a weighted LUT leads to a significant reduction of bone structures in the dark-field image. The weighting of the aluminum component has a substantial impact on the degree to which bone structures remain visible in the dark-field image. Furthermore, a large negative bias in the dark-field image-dependent on the aluminum weighting-was successfully corrected.
conclusionsBH-induced signal in the dark-field images was successfully reduced using the method described. The choice of aluminum weighting to suppress rib structures, as well as the selection of bias correction, should be evaluated based on the specific clinical question.
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