AIMC Topic: Radiation Dosage

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Pediatric evaluations for deep learning CT denoising.

Medical physics Dec 21, 2023
BACKGROUND: Deep learning (DL) CT denoising models have the potential to improve image quality for lower radiation dose exams. These models are generally trained with large quantities of adult patient image data. However, CT, and increasingly DL deno...
Signal-To-Noise Ratio Phantoms, Imaging Tomography, X-Ray Computed Image Processing, Computer-Assisted Infant, Newborn Noise Adult Radiation Dosage Deep Learning Adolescent Child Humans Algorithms
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Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model.

European journal of radiology Dec 19, 2023
PURPOSE: Computed tomography (CT) scans are a significant source of medically induced radiation exposure. Novel deep learning-based denoising (DLD) algorithms have been shown to enable diagnostic image quality at lower radiation doses than iterative ...
Algorithms Tomography, X-Ray Computed Animals Swine Humans Radiation Dosage Deep Learning Radiographic Image Interpretation, Computer-Assisted Models, Animal
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Enhancing cardiac CT imaging quality: Precision metrics for assessing image quality for AI-powered reconstructions.

Diagnostic and interventional imaging Dec 4, 2023
Humans Image Processing, Computer-Assisted Artificial Intelligence Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Algorithms Phantoms, Imaging Tomography, X-Ray Computed
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Deep learning reconstruction for improving the visualization of acute brain infarct on computed tomography.

Neuroradiology Nov 22, 2023
PURPOSE: This study aimed to investigate the impact of deep learning reconstruction (DLR) on acute infarct depiction compared with hybrid iterative reconstruction (Hybrid IR).
Brain Infarction Deep Learning Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Retrospective Studies Tomography, X-Ray Computed Male Humans Algorithms Brain
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Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

Academic radiology Nov 21, 2023
OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3...
Humans Retrospective Studies Female Aged Adult Embolization, Therapeutic Radiation Dosage Cone-Beam Computed Tomography Signal-To-Noise Ratio Radiography, Interventional Radiographic Image Interpretation, Computer-Assisted Male Artifacts Radiation Exposure Middle Aged Deep Learning Bronchial Arteries
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Re-UNet: a novel multi-scale reverse U-shape network architecture for low-dose CT image reconstruction.

Medical & biological engineering & computing Nov 20, 2023
In recent years, the growing awareness of public health has brought attention to low-dose computed tomography (LDCT) scans. However, the CT image generated in this way contains a lot of noise or artifacts, which make increasing researchers to investi...
Radiation Dosage Signal-To-Noise Ratio Algorithms Tomography, X-Ray Computed Image Processing, Computer-Assisted Neural Networks, Computer
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Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study.

Diagnostic and interventional imaging Nov 8, 2023
PURPOSE: The purpose of this study was to compare the performance of Precise IQ Engine (PIQE) and Advanced intelligent Clear-IQ Engine (AiCE) algorithms on image-quality according to the dose level in a cardiac computed tomography (CT) protocol.
Phantoms, Imaging Algorithms Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Humans
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Task-based assessment of resolution properties of CT images with a new index using deep convolutional neural network.

Radiological physics and technology Nov 6, 2023
In this study, we propose a method for obtaining a new index to evaluate the resolution properties of computed tomography (CT) images in a task-based manner. This method applies a deep convolutional neural network (DCNN) machine learning system train...
Tomography, X-Ray Computed Image Processing, Computer-Assisted Radiation Dosage Neural Networks, Computer Algorithms Phantoms, Imaging Tomography Scanners, X-Ray Computed
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Super-resolution deep learning reconstruction at coronary computed tomography angiography to evaluate the coronary arteries and in-stent lumen: an initial experience.

BMC medical imaging Oct 30, 2023
A super-resolution deep learning reconstruction (SR-DLR) algorithm trained using data acquired on the ultrahigh spatial resolution computed tomography (UHRCT) has the potential to provide better image quality of coronary arteries on the whole-heart, ...
Computed Tomography Angiography Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Heart Atria Aged Stents Humans Male Coronary Vessels Algorithms Deep Learning Radiation Dosage Tomography, X-Ray Computed
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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.

Radiological physics and technology Oct 28, 2023
This study aimed to evaluate the ability of deep learning reconstruction (DLR) compared to that of hybrid iterative reconstruction (IR) to depict small vessels on computed tomography (CT). DLR and two types of hybrid IRs were used for image reconstru...
Tomography, X-Ray Computed Deep Learning Radiographic Image Interpretation, Computer-Assisted Algorithms Retrospective Studies Neuroimaging Radiation Dosage Computed Tomography Angiography
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