ArticleThe British journal of radiology2022
Application of deep learning image reconstruction in low-dose chest CT scan.
Article in The British journal of radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Image-Domain GAN Denoising for Sn100 kVp Ultra-Low-Dose Chest CT: A Retrospective Paired Image-Quality Study.Diagnostics (Basel, Switzerland) · 2026Article
- Comparison of DLIR-H and ASIR algorithms for image reconstruction in low-dose chest CT of pediatric mycoplasma pneumoniae pneumonia: a cross-sectional study.Translational pediatrics · 2026Article
- Uncertainty-Aware Framework for CT Radiation Dose Optimization in the Active Surveillance of Small Renal Masses: Clinical and Radiological Considerations.Diagnostics (Basel, Switzerland) · 2026Article
- Efficiency of Artificial Intelligence in Three-Dimensional Reconstruction of Medical Imaging.Cureus · 2025Review
- Quantitative Evaluation of Low-Dose CT Image Quality Using Deep Learning Reconstruction: A Comparative Study of Philips Precise Image and GE TrueFidelity.Journal of imaging · 2025Article
- Deep learning-based image domain reconstruction enhances image quality and pulmonary nodule detection in ultralow-dose CT with adaptive statistical iterative reconstruction-V.European radiology · 2025Article
- Feature Reviews for Tomography 2023.Tomography (Ann Arbor, Mich.) · 2024Article
- Value of deep learning reconstruction of chest low-dose CT for image quality improvement and lung parenchyma assessment on lung window.European radiology · 2024Article
- Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT.PloS one · 2024Article
- Ultra-High-Resolution CT of the Head and Neck with Deep Learning Reconstruction-Assessment of Image Quality and Radiation Exposure and Intraindividual Comparison with Normal-Resolution CT.Diagnostics (Basel, Switzerland) · 2023Article
- Deep learning image reconstruction algorithm: impact on image quality in coronary computed tomography angiography.La Radiologia medica · 2023Article
- Radiation dose reduction using deep learning-based image reconstruction for a low-dose chest computed tomography protocol: a phantom study.Quantitative imaging in medicine and surgery · 2023Article
- Innovations in thoracic imaging: CT, radiomics, AI and x-ray velocimetry.Respirology (Carlton, Vic.) · 2022Review
- Artificial Intelligence in Chest Computed Tomography Optimization: A Task-based Framework for Balancing Detectability and Radiation Dose.Journal of medical physicsReview
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5 authors.
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Abstract
objectiveDeep learning image reconstruction (DLIR) is a new reconstruction method for maintaining image quality at reduced radiation dose. The purpose of this study was to compare image quality of reduced-dose DLIR images with the standard-dose adaptive statistical iterative reconstruction (ASIR-V) images in chest CT.
methodsOur prospective study included 48 adult patients (30 women and 18 men, mean age ±SD, 49.8 ± 14.3 years) who underwent both the standard-dose CT (SDCT) and low-dose CT (LDCT) on a GE Revolution CT scanner. All patients gave written informed consent. All scans were reconstructed with ASIR-V40%. Additionally, LDCT scans were reconstructed with DLIR with high-setting (DLIR-H) and medium-setting (DLIR-M). Image noise and contrast-noise-ratio (CNR) of thoracic aorta with different reconstruction modes were measured and compared.
resultsLDCT reduced radiation dose by 96% compared with SDCT (CTDIvol: 0.54mGy
conclusionDLIR significantly reduces image noise in LDCT chest scans and provides similar image quality as the SDCT ASIR-V images at 4% of the radiation dose. ADVANCES IN KNOWLEDGE: DLIR uses high-quality FBP data to train deep neural networks to learn how to distinguish between signal and noise, and effectively suppresses noise without affecting anatomical and pathological structures. It opens a new era of CT image reconstruction. DLIR significantly reduces image noise and improves image quality compared with ASIR-V40% under same radiation dose condition. DLIR-H achieves similar image quality at 4% radiation dose as ASIR-V40% at standard-dose level in non-contrast chest CT.
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