ArticleBMC medical imaging2023
Image quality comparison of lower extremity CTA between CT routine reconstruction algorithms and deep learning reconstruction.
Article in BMC medical imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- Vendor-agnostic versus vendor-specific boost methods in low-concentration contrast-enhanced computed tomography of the abdomen.Quantitative imaging in medicine and surgery · 2026Article
- Myocardial extracellular volume fraction in cardiac CT: comparison of deep learning reconstruction and iterative reconstruction.Journal of thoracic disease · 2026Article
- Automatic segmentation and reconstruction of lower-extremity arteries from computed tomography angiography images via a deep learning framework.Quantitative imaging in medicine and surgery · 2025Article
- Deep learning reconstruction for improved image quality of ultra-high-resolution brain CT angiography: application in moyamoya disease.Japanese journal of radiology · 2025Article
- Current imaging applications, radiomics, and machine learning modalities of CNS demyelinating disorders and its mimickers.Journal of neurology · 2025Review
- Clinical comparison of transfemoral vs. distal transradial access for lower extremity arteriography.Frontiers in surgery · 2025Review
- A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.BMC medical imaging · 2024Article
- Three-dimensional CT imaging in extensor tendons using deep learning reconstruction: optimal reconstruction parameters and the influence of dose.Physical and engineering sciences in medicine · 2023Article
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10 authors.
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Abstract
backgroundTo evaluate the image quality of lower extremity computed tomography angiography (CTA) with deep learning-based reconstruction (DLR) compared to model-based iterative reconstruction (MBIR), hybrid-iterative reconstruction (HIR), and filtered back projection (FBP).
methodsFifty patients (38 males, average age 59.8 ± 19.2 years) who underwent lower extremity CTA between January and May 2021 were included. Images were reconstructed with DLR, MBIR, HIR, and FBP. The standard deviation (SD), contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), noise power spectrum (NPS) curves, and the blur effect, were calculated. The subjective image quality was independently evaluated by two radiologists. The diagnostic accuracy of DLR, MBIR, HIR, and FBP reconstruction algorithms was calculated.
resultsThe CNR and SNR were significantly higher in DLR images than in the other three reconstruction algorithms, and the SD was significantly lower in DLR images of the soft tissues. The noise magnitude was the lowest with DLR. The NPS average spatial frequency (f
conclusionsCompared to the other three reconstruction algorithms, DLR showed better objective and subjective image quality. The blur effect of the DLR was better than that of the HIR. The diagnostic accuracy of lower extremity CTA with DLR was the best among the four reconstruction algorithms.
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