AIMC Topic: Radiation Dosage

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Can deep learning improve image quality of low-dose CT: a prospective study in interstitial lung disease.

European radiology
OBJECTIVES: To investigate whether deep learning reconstruction (DLR) could keep image quality and reduce radiation dose in interstitial lung disease (ILD) patients compared with HRCT reconstructed with hybrid iterative reconstruction (hybrid-IR).

Impact of an artificial intelligence deep-learning reconstruction algorithm for CT on image quality and potential dose reduction: A phantom study.

Medical physics
BACKGROUND: Recently, computed tomography (CT) manufacturers have developed deep-learning-based reconstruction algorithms to compensate for the limitations of iterative reconstruction (IR) algorithms, such as image smoothing and the spatial resolutio...

Lung-Optimized Deep-Learning-Based Reconstruction for Ultralow-Dose CT.

Academic radiology
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
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...

Pulmonary emphysema quantification at low dose chest CT using Deep Learning image reconstruction.

European journal of radiology
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...