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Deep learning reconstruction for high-resolution computed tomography images of the temporal bone: comparison with hybrid iterative reconstruction
PurposeWe investigated whether the quality of high-resolution computed tomography (CT) images of the temporal bone improves with deep learning...
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Improving the depiction of small intracranial vessels in head computed tomography angiography: a comparative analysis of deep learning reconstruction and hybrid iterative reconstruction
This study aimed to evaluate the ability of deep learning reconstruction (DLR) compared to that of hybrid iterative reconstruction (IR) to depict...
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Truncation effect reduction for fast iterative reconstruction in cone-beam CT
BackgroundIterative reconstruction for cone-beam computed tomography (CBCT) has been applied to improve image quality and reduce radiation dose. In a...
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Quantum iterative reconstruction on a photon-counting detector CT improves the quality of hepatocellular carcinoma imaging
BackgroundExcellent image quality is crucial for workup of hepatocellular carcinoma (HCC) in patients with liver cirrhosis because a signature tumor...
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Utility of follow-up ultra-high-resolution CT angiography with model-based iterative reconstruction after flow diverter treatment for cerebral aneurysms
PurposeFollow-up examinations after flow diverter (FD) treatment for cerebral aneurysms typically involve magnetic resonance imaging (MRI) or digital...
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Impacts of Adaptive Statistical Iterative Reconstruction-V and Deep Learning Image Reconstruction Algorithms on Robustness of CT Radiomics Features: Opportunity for Minimizing Radiomics Variability Among Scans of Different Dose Levels
This study aims to investigate the influence of adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction...
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Iterative Motion Correction Technique with Deep Learning Reconstruction for Brain MRI: A Volunteer and Patient Study
The aim of this study was to investigate the effect of iterative motion correction (IMC) on reducing artifacts in brain magnetic resonance imaging...
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Deep learning image reconstruction algorithm reduces image noise while alters radiomics features in dual-energy CT in comparison with conventional iterative reconstruction algorithms: a phantom study
ObjectivesTo compare image quality between a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR)...
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Low Dose Pediatric CT Head Protocol using Iterative Reconstruction Techniques: A Comparison with Standard Dose Protocol
PurposePediatric computed tomography (CT) head examination has also increased in recent years with the advancement in CT technology; however,...
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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
PurposeTo examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced...
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Phantom and clinical evaluation of the effect of a new Bayesian penalized likelihood reconstruction algorithm (HYPER Iterative) on 68Ga-DOTA-NOC PET/CT image quality
BackgroundBayesian penalized likelihood (BPL) algorithm is an effective way to suppress noise in the process of positron emission tomography (PET)...
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Low-dose contrast-enhanced time-resolved angiography with stochastic trajectories with iterative reconstruction (IT-TWIST-MRA) in brain arteriovenous shunt
ObjectivesTo assess the feasibility of low-dose contrast-enhanced four-dimensional (4D) time-resolved angiography with stochastic trajectories...
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Deep learning-based PET image denoising and reconstruction: a review
This review focuses on positron emission tomography (PET) imaging algorithms and traces the evolution of PET image reconstruction methods. First, we...
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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)
PurposeTo compare the effects of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction V (ASiR-V) on image...
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Visualization of thrombus using iterative reconstruction and maximum intensity projection of thin-slice CT images
ObjectiveIterative reconstruction (IR) is a noise reduction method that facilitates the synthesis of maximum intensity projection (MIP) from a larger...
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Application of Deep Learning-Based Denoising Technique for Radiation Dose Reduction in Dynamic Abdominal CT: Comparison with Standard-Dose CT Using Hybrid Iterative Reconstruction Method
The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient image quality for abdominal computed tomography...
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Deep learning versus iterative image reconstruction algorithm for head CT in trauma
PurposeTo compare the image quality between a deep learning–based image reconstruction algorithm (DLIR) and an adaptive statistical iterative...
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Image quality comparison of lower extremity CTA between CT routine reconstruction algorithms and deep learning reconstruction
BackgroundTo evaluate the image quality of lower extremity computed tomography angiography (CTA) with deep learning–based reconstruction (DLR)...
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Deep learning image reconstruction for pancreatic low-dose computed tomography: comparison with hybrid iterative reconstruction
PurposeTo evaluate image quality, image noise, and conspicuity of pancreatic ductal adenocarcinoma (PDAC) in pancreatic low-dose computed tomography...
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Deep learning reconstruction vs standard reconstruction for abdominal CT: the influence of BMI
ObjectiveThis study aimed to evaluate the image quality and lesion conspicuity of the deep learning image reconstruction (DLIR) algorithm compared...
