AIMC Topic: Radiography, Dual-Energy Scanned Projection

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Evaluating renal lesions using deep-learning based extension of dual-energy FoV in dual-source CT-A retrospective pilot study.

European journal of radiology Apr 24, 2021
PURPOSE: Dual-source (DS) CT, dual-energy (DE) field of view (FoV) is limited to the size of the smaller detector array. The purpose was to establish a deep learning-based approach to DE extrapolation by estimating missing image data using data from ...
Pilot Projects Kidney Contrast Media Tomography, X-Ray Computed Reproducibility of Results Deep Learning Radiography, Dual-Energy Scanned Projection Humans Retrospective Studies
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Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique.

European radiology Oct 8, 2020
OBJECTIVES: To evaluate the image quality of low iodine concentration, dual-energy CT (DECT) combined with a deep learning-based noise reduction technique for pediatric abdominal CT, compared with standard iodine concentration single-energy polychrom...
Child Contrast Media Signal-To-Noise Ratio Radiography, Dual-Energy Scanned Projection Deep Learning Adolescent Child, Preschool Young Adult Adult Male Humans Retrospective Studies Tomography, X-Ray Computed Female
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Liver lesion localisation and classification with convolutional neural networks: a comparison between conventional and spectral computed tomography.

Biomedical physics & engineering express Jan 30, 2020
PURPOSE: To evaluate the benefit of the additional available information present in spectral CT datasets, as compared to conventional CT datasets, when utilizing convolutional neural networks for fully automatic localisation and classification of liv...
Liver Diseases Signal-To-Noise Ratio Radiography, Dual-Energy Scanned Projection Humans Algorithms Neural Networks, Computer Tomography, X-Ray Computed Machine Learning Radiographic Image Interpretation, Computer-Assisted
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Automatic multi-organ segmentation in dual-energy CT (DECT) with dedicated 3D fully convolutional DECT networks.

Medical physics Jan 1, 2020
PURPOSE: Dual-energy computed tomography (DECT) has shown great potential in many clinical applications. By incorporating the information from two different energy spectra, DECT provides higher contrast and reveals more material differences of tissue...
Humans Tomography, X-Ray Computed Lung Deep Learning Image Processing, Computer-Assisted Kidney Dose-Response Relationship, Radiation Radiography, Dual-Energy Scanned Projection Signal-To-Noise Ratio Abdomen Spleen Models, Theoretical Thorax Liver
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Deep learning-based virtual noncontrast CT for volumetric modulated arc therapy planning: Comparison with a dual-energy CT-based approach.

Medical physics Dec 3, 2019
PURPOSE: The aim of this study was to develop a deep learning (DL) method for generating virtual noncontrast (VNC) computed tomography (CT) images from contrast-enhanced (CE) CT images (VNC ) and to evaluate its performance in dose calculations for h...
Neck Radiotherapy, Intensity-Modulated Contrast Media Humans Deep Learning Head Radiographic Image Enhancement Tomography, X-Ray Computed Iodine Radiography, Dual-Energy Scanned Projection Reproducibility of Results Time Factors
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Quantitative CT biomarkers for renal cell carcinoma subtype differentiation: a comparison of DECT, PCT, and CT texture analysis.

The British journal of radiology Jul 1, 2025
OBJECTIVE: To evaluate and compare the diagnostic performance of CT texture analysis (CTTA), perfusion CT (PCT), and dual-energy CT (DECT) in distinguishing between clear-cell renal cell carcinoma (ccRCC) and non-ccRCC.
Aged, 80 and over Adult Male Tomography, X-Ray Computed Female Aged Kidney Neoplasms Humans Carcinoma, Renal Cell Machine Learning Radiography, Dual-Energy Scanned Projection Retrospective Studies Middle Aged Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted
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Conversion of single-energy CT to parametric maps of dual-energy CT using convolutional neural network.

The British journal of radiology May 29, 2024
OBJECTIVES: We propose a deep learning (DL) multitask learning framework using convolutional neural network for a direct conversion of single-energy CT (SECT) to 3 different parametric maps of dual-energy CT (DECT): virtual-monochromatic image (VMI),...
Tomography, X-Ray Computed Deep Learning Radiography, Dual-Energy Scanned Projection Humans Neural Networks, Computer
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Performance evaluation of deep learning image reconstruction algorithm for dual-energy spectral CT imaging: A phantom study.

Journal of X-ray science and technology Jan 1, 2024
OBJECTIVES: To evaluate the performance of deep learning image reconstruction (DLIR) algorithm in dual-energy spectral CT (DEsCT) as a function of radiation dose and image energy level, in comparison with filtered-back-projection (FBP) and adaptive s...
Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Humans Algorithms Radiography, Dual-Energy Scanned Projection Radiation Dosage Signal-To-Noise Ratio Phantoms, Imaging
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Multi-material decomposition of spectral CT images via Fully Convolutional DenseNets.

Journal of X-ray science and technology Jan 1, 2019
BACKGROUND: Spectral computed tomography (CT) has the capability to resolve the energy levels of incident photons, which has the potential to distinguish different material compositions. Although material decomposition methods based on x-ray attenuat...
Signal-To-Noise Ratio Image Processing, Computer-Assisted Tomography, X-Ray Computed Photons Mice Animals Radiography, Dual-Energy Scanned Projection Calibration Deep Learning
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