ArticleMedical physics2026
Estimation of proton stopping power from principal components of dual-energy CT virtual monoenergetic images.
Article in Medical physics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundDECT systems can perform projection-domain decomposition to generate quantitative maps of electron density ( PURPOSE: To develop and evaluate a principal component analysis (PCA)-based method that optimally combines the full set of VMIs into a single image pair for estimating
methodsPCA is applied to CT numbers of tissue-equivalent inserts across VMIs reconstructed at 50-200 keV to derive two independent component images, which are used as input to SPR estimation frameworks. Performance is evaluated on a tissue-equivalent phantom using leave-one-out cross-validation and further assessed on realistic simulated patient CT datasets. Results are compared with conventional VMI pairs, polyenergetic images, and single-energy CT (SECT) methods.
resultsIn the phantom study, the PCA-based method reduced RMS errors in
conclusionsThe proposed PCA-based strategy provides a VMI input pair by combining all available VMIs along principal component directions, producing images that can be used for accurate
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