ArticleEuropean radiology2023
Evaluation of the impact of a novel denoising algorithm on image quality in dual-energy abdominal CT of obese patients.
Article in European radiology, 2023. 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.
- Denoising pediatric cardiac photon-counting CT data with sparse coding and data-adaptive, self-supervised deep learning.Medical physics · 2025Article
- Research Progress of Dual-energy CT in Diagnosis and Evaluation of Curative Effect of Liver Cancer: A ReviewCurrent medical imaging · 2025Review
- Clinical application of high-resolution spiral CT scanning in the diagnosis of auriculotemporal and ossicle.BMC medical imaging · 2024Article
- Quality assessment of abdominal CT images: an improved ResNet algorithm with dual-attention mechanism.American journal of translational research · 2024Article
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Authors and funding
9 authors.
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Abstract
objectivesEvaluate a novel algorithm for noise reduction in obese patients using dual-source dual-energy (DE) CT imaging.
methodsSeventy-nine patients with contrast-enhanced abdominal imaging (54 women; age: 58 ± 14 years; BMI: 39 ± 5 kg/m
resultsAverage CNR was 5.0 ± 1.9 (original), 31.1 ± 10.3 (comparison; p < 0.001), and 8.9 ± 2.9 (test; p < 0.001). Readers were in good to moderate agreement over perceived image noise (ICC: 0.83), image quality (ICC: 0.71), and diagnostic comfort (ICC: 0.6). Diagnostic accuracy was low across algorithms (accuracy: 66, 63, and 67% (original, comparison, test)). The noise received a mean score of 54, 84, and 66 (p < 0.05); image quality 59, 61, and 65; and the diagnostic comfort 63, 68, and 68, respectively. Quality and comfort scores were not statistically significantly different between algorithms.
conclusionsThe test algorithm produces quantitatively higher image quality than current standard and existing denoising algorithms in obese patients imaged with DECT and readers show a preference for it. CLINICAL RELEVANCE STATEMENT: Accurate diagnosis on CT imaging of obese patients is challenging and denoising algorithms can increase the diagnostic comfort and quantitative image quality. This could lead to better clinical reads. KEY POINTS: • Improving image quality in DECT imaging of obese patients is important for accurate and confident clinical reads, which may be aided by novel denoising algorithms using image domain data. • Accurate diagnosis on CT imaging of obese patients is especially challenging and denoising algorithms can increase quantitative and qualitative image quality. • Image domain algorithms can generalize well and can be implemented at other institutions.
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