AIMC Topic: Radiation Dosage
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Accuracy of two deep learning-based reconstruction methods compared with an adaptive statistical iterative reconstruction method for solid and ground-glass nodule volumetry on low-dose and ultra-low-dose chest computed tomography: A phantom study.
PloS one
Jun 23, 2022
No published studies have evaluated the accuracy of volumetric measurement of solid nodules and ground-glass nodules on low-dose or ultra-low-dose chest computed tomography, reconstructed using deep learning-based algorithms. This is an important iss...
Lung-Optimized Deep-Learning-Based Reconstruction for Ultralow-Dose CT.
Academic radiology
Jun 20, 2022
RATIONALE AND OBJECTIVES: To evaluate the image properties of lung-specialized deep-learning-based reconstruction (DLR) and its applicability in ultralow-dose CT (ULDCT) relative to hybrid- (HIR) and model-based iterative-reconstructions (MBIR).
Dose length product and outcome of CT fluoroscopy-guided interventions using a new 320-detector row CT scanner with deep-learning reconstruction and new bow-tie filter.
The British journal of radiology
Jun 15, 2022
OBJECTIVES: To investigate the dose length product (DLP) and outcomes of CT fluoroscopy (CTF)-guided interventions using a novel 320-detector row CT scanner with deep-learning reconstruction (DLR) and a new bow-tie filter ( Aquilion ONE Prism Edition...
Clinical validation of an AI-based motion correction reconstruction algorithm in cerebral CT.
European radiology
Jun 9, 2022
OBJECTIVES: To evaluate the clinical performance of an artificial intelligence (AI)-based motion correction (MC) reconstruction algorithm for cerebral CT.
Assessment of low-dose paranasal sinus CT imaging using a new deep learning image reconstruction technique in children compared to adaptive statistical iterative reconstruction V (ASiR-V).
BMC medical imaging
Jun 3, 2022
PURPOSE: To compare the effects of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASiR-V) on image quality in low-dose computed tomography (CT) of paranasal sinuses in children.
Comparison of a Deep Learning-Based Reconstruction Algorithm with Filtered Back Projection and Iterative Reconstruction Algorithms for Pediatric Abdominopelvic CT.
Korean journal of radiology
May 27, 2022
OBJECTIVE: To compare a deep learning-based reconstruction (DLR) algorithm for pediatric abdominopelvic computed tomography (CT) with filtered back projection (FBP) and iterative reconstruction (IR) algorithms.
Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.
European journal of radiology
May 5, 2022
PURPOSE: Quantitative analysis of emphysema volume is affected by the radiation dose and the CT reconstruction technique. We aim to evaluate the influence of a commercially available deep learning image reconstruction algorithm (DLIR) on the quantifi...
Image Quality Evaluation in Dual-Energy CT of the Chest, Abdomen, and Pelvis in Obese Patients With Deep Learning Image Reconstruction.
Journal of computer assisted tomography
Apr 27, 2022
OBJECTIVE: The aim of this study was to evaluate image quality in vascular and oncologic dual-energy computed tomography (CT) imaging studies performed with a deep learning (DL)-based image reconstruction algorithm in patients with body mass index of...
A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation.
Clinical radiology
Apr 9, 2022
AIM: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS).
Evaluation of moyamoya disease in CT angiography using ultra-high-resolution computed tomography: Application of deep learning reconstruction.
European journal of radiology
Apr 9, 2022
PURPOSE: The aim of this study was to examine the evaluation of ultra-high-resolution computed tomography angiography (UHR CTA) images in moyamoya disease (MMD) reconstructed with hybrid iterative reconstruction (Hybrid-IR), model-based iterative rec...
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