AIMC Topic: Radiation Dosage
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Deep learning-based noise reduction for coronary CT angiography: using four-dimensional noise-reduction images as the ground truth.
Acta radiologica (Stockholm, Sweden : 1987)
Dec 7, 2022
BACKGROUND: To assess low-contrast areas such as plaque and coronary artery stenosis, coronary computed tomography angiography (CCTA) needs to provide images with lower noise without increasing radiation doses.
Computed Tomography of the Spine : Systematic Review on Acquisition and Reconstruction Techniques to Reduce Radiation Dose.
Clinical neuroradiology
Nov 22, 2022
The introduction of the first whole-body CT scanner in 1974 marked the beginning of cross-sectional spine imaging. In the last decades, the technological advancement, increasing availability and clinical success of CT led to a rapidly growing number ...
Iterative reconstruction deep learning image reconstruction: comparison of image quality and diagnostic accuracy of arterial stenosis in low-dose lower extremity CT angiography.
The British journal of radiology
Nov 15, 2022
OBJECTIVE: To compare image quality and diagnostic accuracy of arterial stenosis in low-dose lower-extremity CT angiography (CTA) between adaptive statistical iterative reconstruction-V (ASIR-V) and deep learning image reconstruction (DLIR) algorithm...
CT image quality evaluation in the age of deep learning: trade-off between functionality and fidelity.
European radiology
Nov 9, 2022
OBJECTIVE: To quantitatively compare DLIR and ASiR-V with realistic anatomical images.
Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?
European radiology
Nov 3, 2022
OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning image reconstruction (DLIR) with full-dose filtered back projection (FBP)/iterative reconstruction (IR).
Abdominopelvic CT Image Quality: Evaluation of Thin (0.5-mm) Slices Using Deep Learning Reconstruction.
AJR. American journal of roentgenology
Oct 19, 2022
Because thick-section images (typically 3-5 mm) have low image noise, radiologists typically use them to perform clinical interpretation, although they may additionally refer to thin-section images (typically 0.5-0.625 mm) for problem solving. Deep ...
Image quality improvement in low-dose chest CT with deep learning image reconstruction.
Journal of applied clinical medical physics
Oct 9, 2022
OBJECTIVES: To investigate the clinical utility of deep learning image reconstruction (DLIR) for improving image quality in low-dose chest CT in comparison with 40% adaptive statistical iterative reconstruction-Veo (ASiR-V40%) algorithm.
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.
European radiology
Oct 5, 2022
OBJECTIVES: To compare image quality between a deep learning image reconstruction (DLIR) algorithm and conventional iterative reconstruction (IR) algorithms in dual-energy CT (DECT) and to assess the impact of these algorithms on radiomics robustness...
Improving spatial resolution and diagnostic confidence with thinner slice and deep learning image reconstruction in contrast-enhanced abdominal CT.
European radiology
Oct 3, 2022
OBJECTIVE: To evaluate image quality and diagnostic confidence improvement using a thin slice and a deep learning image reconstruction (DLIR) in contrast-enhanced abdominal CT.
Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.
Korean journal of radiology
Sep 29, 2022
OBJECTIVE: This 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 f...
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