ArticleJournal of applied clinical medical physics2019
Noise reduction in dual-energy computed tomography virtual monoenergetic imaging.
Article in Journal of applied clinical medical physics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Dual-energy CT-based virtual monoenergetic imaging via unsupervised learning.Physical and engineering sciences in medicine · 2025Article
- Dual-Energy Computed Tomography in Stroke Imaging : Value of a New Image Acquisition Technique for Ischemia Detection after Mechanical Thrombectomy.Clinical neuroradiology · 2023Article
- Image-Quality Assessment of Polyenergetic and Virtual Monoenergetic Reconstructions of Unenhanced CT Scans of the Head: Initial Experiences with the First Photon-Counting CT Approved for Clinical Use.Diagnostics (Basel, Switzerland) · 2022Article
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2 authors.
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Abstract
purposeVirtual monoenergetic images (VMIs) derived from dual-energy computed tomography (DECT) have been explored for several clinical applications in recent years. However, VMIs at low and high keVs have high levels of noise. The aim of this study was to reduce image noise in VMIs by using a two-step noise reduction technique.
methodsVMI was first denoised using a modified highly constrained backprojection (HYPR) method. After the first-step denoising, a general-threshold filtering method was performed. Two sets of anthropomorphic phantoms were scanned with a clinical dual-source DECT system. DECT data (80/140Sn kV) were reconstructed as VMI series at 12 different energy levels (range, 40-150 keV, interval, 10 keV). For comparison, the averaged VMIs obtained from 10 repeated DECT scans were used as the reference standard. The signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and root-mean-square error (RMSE) were used to evaluate the quality of VMIs.
resultsCompared to the original HYPR method, the proposed two-step image denoising method could provide better performance in terms of SNR, CNR, and RMSE. In addition, the proposed method could achieve effective noise reduction while preserving edges and small structures, especially for low-keV VMIs.
conclusionThe proposed two-step image denoising method is a feasible method for reducing noise in VMIs obtained from a clinical DECT scanner. The proposed method can also reduce edge blurring and the loss of intensity in small lesions.
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