ArticleQuantitative imaging in medicine and surgery2022
Comparison of virtual monoenergetic imaging between a rapid kilovoltage switching dual-energy computed tomography with deep-learning and four dual-energy CTs with iterative reconstruction.
Article in Quantitative imaging in medicine and surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 32 citations in OpenAlex.
- Accuracy of iodine quantification and CT numbers using split-filter dual-energy CT: influence of phantom diameter.Physical and engineering sciences in medicine · 2026Article
- [Dual-energy CT for differential diagnosis of adrenal lesions].Problemy endokrinologii · 2025Article
- Impact of a prototype, dedicated AI-based spectral image reconstruction algorithm on the quality of low-keV virtual monoenergetic images and iodine maps: A phantom study.Medical physics · 2025Article
- Contrast medium dose optimization in the era of multi-energy CT.Japanese journal of radiology · 2025Review
- Comparing two deep learning spectral reconstruction levels for abdominal evaluation using a rapid-kVp-switching dual-energy CT scanner.Abdominal radiology (New York) · 2025Article
- Dual-energy computed tomography with new virtual monoenergetic image reconstruction enhances prostate lesion image quality and improves the diagnostic efficacy for prostate cancer.BMC medical imaging · 2024Article
- Determining the Optimal Energy Level of Virtual Monoenergetic Images in Dual-Source CT for Diagnosis of Bowel Obstruction and Colitis.Diagnostics (Basel, Switzerland) · 2023Article
- Impact of Phantom Size on Low-Energy Virtual Monoenergetic Images of Three Dual-Energy CT Platforms.Diagnostics (Basel, Switzerland) · 2023Article
- Improved Coronary Artery Visualization Using Virtual Monoenergetic Imaging from Dual-Layer Spectral Detector CT Angiography.Diagnostics (Basel, Switzerland) · 2023Article
- Comparison of image quality of two versions of deep-learning image reconstruction algorithm on a rapid kV-switching CT: a phantom study.European radiology experimental · 2023Article
- Radiomics-Based Machine Learning for Predicting the Injury Time of Rib Fractures in Gemstone Spectral Imaging Scans.Bioengineering (Basel, Switzerland) · 2022Article
- Spectral CT in peritoneal carcinomatosis from ovarian cancer: a tool for differential diagnosis of small nodules?European radiology experimental · 2022Article
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Authors and funding
9 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo assess the spectral performance of rapid kV switching dual-energy CT (KVSCT-Canon) equipped with a Deep-Learning spectral reconstruction algorithm on virtual-monoenergetic images at low-energy levels and to compare its performances with four other dual-energy CT (DECT) platforms equipped with iterative reconstruction algorithms.
methodsTwo CT phantoms were scanned on five DECT platforms: KVSCT-Canon, fast kV-switching CT (KVSCT-GE), split filter CT, dual-source CT (DSCT), and dual-layer CT (DLCT). The classical parameters of abdomen-pelvic examinations were used for all phantom acquisitions, and a CTDI
resultsFor KVSCT-Canon, the noise magnitude and average NPS spatial frequency (f
conclusionsFor KVSCT-Canon, the detectability of contrast-enhanced lesions was highest at 60 keV. The highest d' values were found for DLCT at 40 and 50 keV and for KVSCT-Canon at 1.5 mm for other keV.
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