ArticleDiagnostics (Basel, Switzerland)2021
Deep Learning-Based Image Reconstruction for CT Angiography of the Aorta.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 21 citations in OpenAlex.
- Deep-learning based image reconstruction enables reduced dose CT pulmonary angiography with non-inferior image quality.Scientific reports · 2026Article
- Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on automated Alberta stroke program early CT score- evaluation.Neuroradiology · 2026Article
- Application of Deep Learning Algorithm-Based Image Reconstruction in Improving Abdominal CT Image Quality in Adrenal and Renal Lesions Detection.Radiology research and practice · 2026Article
- Improved CTA imaging for stroke evaluation - deep learning and iterative reconstruction comparative study.Neuroradiology · 2025Article
- Artificial intelligence in aortic CT angiography: current applications and future perspectives.Frontiers in cardiovascular medicine · 2025Review
- Improved vascular depiction and image quality through deep learning reconstruction of CT hepatic arteriography during transcatheter arterial chemoembolization.Japanese journal of radiology · 2024Article
- Large vessel vasculitis evaluation by CTA: impact of deep-learning reconstruction and "dark blood" technique.Insights into imaging · 2024Article
- Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction.Scientific reports · 2024Article
- Clinical Feasibility of Deep Learning-Based Image Reconstruction on Coronary Computed Tomography Angiography.Journal of clinical medicine · 2023Article
- Deep learning image reconstruction algorithm: impact on image quality in coronary computed tomography angiography.La Radiologia medica · 2023Article
- Improved image quality in transcatheter aortic valve implantation planning CT using deep learning-based image reconstruction.Quantitative imaging in medicine and surgery · 2023Article
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6 authors at 1 institution in 1 country.
Funding
Abstract
To evaluate the impact of a novel, deep-learning-based image reconstruction (DLIR) algorithm on image quality in CT angiography of the aorta, we retrospectively analyzed 51 consecutive patients who underwent ECG-gated chest CT angiography and non-gated acquisition for the abdomen on a 256-dectector-row CT. Images were reconstructed with adaptive statistical iterative reconstruction (ASIR-V) and DLIR. Intravascular image noise, the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) were quantified for the ascending aorta, the descending thoracic aorta, the abdominal aorta and the iliac arteries. Two readers scored subjective image quality on a five-point scale. Compared to ASIR-V, DLIR reduced the median image noise by 51-54% for the ascending aorta and the descending thoracic aorta. Correspondingly, median CNR roughly doubled for the ascending aorta and descending thoracic aorta. There was a 38% reduction in image noise for the abdominal aorta and the iliac arteries, with a corresponding improvement in CNR. Median subjective image quality improved from good to excellent at all anatomical levels. In CT angiography of the aorta, DLIR substantially improved objective and subjective image quality beyond what can be achieved by state-of-the-art iterative reconstruction. This can pave the way for further radiation or contrast dose reductions.
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