ArticleKorean journal of radiology2022
Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.
Article in Korean journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 31 citations in OpenAlex.
- Deep Learning-Based Augmented Contrast-Enhancement and Denoising for Reduced-Iodine and Low-Radiation 70-kVp Cerebral CT Angiography: A Prospective Study.Korean journal of radiology · 2026Trial
- Deep Learning-Based Image Reconstruction in Ultra-High-Resolution CT Venography for Improved Visualization of Cerebral Venous Drainage.Clinical neuroradiology · 2026Article
- Clinical value of dual low-dose computed tomography angiography incorporating artificial intelligence iterative reconstruction for assessing arteriovenous fistulas/grafts among hemodialysis patients.Quantitative imaging in medicine and surgery · 2026Article
- Clinical Applications of Artificial Intelligence in Cardiovascular Imaging: Where Do We Stand?Life (Basel, Switzerland) · 2026Review
- Quantitative and qualitative assessment of ultra-low-dose paranasal sinus CT using deep learning image reconstruction: a comparison with hybrid iterative reconstruction.European radiology · 2025Article
- Detection of intracranial hemorrhage using ultralow-dose brain computed tomography with deep learning reconstruction versus conventional-dose computed tomography.BMC medical imaging · 2025Article
- Effectiveness of wedge filter application in reducing lens radiation dose during diagnostic cerebral angiography: a phantom and prospective study.European radiology · 2025Article
- Conceptual review of outcome metrics and measures used in clinical evaluation of artificial intelligence in radiology.La Radiologia medica · 2024Review
- Super-resolution deep learning image reconstruction: image quality and myocardial homogeneity in coronary computed tomography angiography.Journal of cardiovascular imaging · 2024Article
- Revolutionizing Cardiac Imaging: A Scoping Review of Artificial Intelligence in Echocardiography, CTA, and Cardiac MRI.Journal of imaging · 2024Article
- A preliminary study of super-resolution deep learning reconstruction with cardiac option for evaluation of endovascular-treated intracranial aneurysms.The British journal of radiology · 2024Article
- Improved stent sharpness evaluation with super-resolution deep learning reconstruction in coronary CT angiography.The British journal of radiology · 2024Article
- Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.Korean journal of radiology · 2024Article
- Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis.Korean journal of radiology · 2024Article
- Effect of deep learning image reconstruction with high-definition standard scan mode on image quality of coronary stents and arteries.Quantitative imaging in medicine and surgery · 2024Article
- Artificial Intelligence in the Screening, Diagnosis, and Management of Aortic Stenosis.Reviews in cardiovascular medicine · 2024Review
- Article
- Improving image quality with super-resolution deep-learning-based reconstruction in coronary CT angiography.European radiology · 2023Article
- Reporting Quality of Research Studies on AI Applications in Medical Images According to the CLAIM Guidelines in a Radiology Journal With a Strong Prominence in Asia.Korean journal of radiology · 2023Review
- Reduction of Radiation Dose to Eye Lens in Cerebral 3D Rotational Angiography Using Head Off-Centering by Table Height Adjustment: A Prospective Study.Korean journal of radiology · 2023Article
Corrections and comments
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Authors and funding
7 authors at 6 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visibility of the valve apparatus in coronary computed tomography angiography (CCTA) when compared with filtered back projection (FBP) and hybrid iterative reconstruction (IR) methods. MATERIALS AND
methodsCCTA images of 51 patients (mean age ± standard deviation [SD], 63.9 ± 9.8 years, 36 male) who underwent examination at a single institution were reconstructed using DLR, FBP, and hybrid IR methods and reviewed. CT attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and stent evaluation, including 10%-90% edge rise slope (ERS) and 10%-90% edge rise distance (ERD), were measured. Quantitative data are summarized as the mean ± SD. The subjective visual scores (1 for worst -5 for best) of the images were obtained for the following: overall image quality, image noise, and appearance of stent, vessel, and aortic and tricuspid valve apparatus (annulus, leaflets, papillary muscles, and chordae tendineae). These parameters were compared between the DLR, FBP, and hybrid IR methods.
resultsDLR provided higher Hounsfield unit (HU) values in the aorta and similar attenuation in the fat and muscle compared with FBP and hybrid IR. The image noise in HU was significantly lower in DLR (12.6 ± 2.2) than in hybrid IR (24.2 ± 3.0) and FBP (54.2 ± 9.5) (
conclusionDLR reconstruction provided better images than FBP and hybrid IR reconstruction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.