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Keyphrases
Dual-energy CT
100%
Deep Convolutional Neural Network (deep CNN)
100%
Stopping Power
100%
Power Graph
100%
Relative Stopping Power
87%
Deep Learning
25%
Mean Error
25%
Physics-based
25%
Mean Absolute Error
25%
Lung
12%
Physical Properties
12%
Head-and-neck Cancer
12%
Clinical Application
12%
Soft Tissue
12%
Cancer Patients
12%
CT Images
12%
Image Quality
12%
Mapping Method
12%
Tissue Type
12%
Parameter Dependence
12%
Noise Level
12%
Image Noise
12%
Dual Energy
12%
Map-based
12%
Number of Parameters
12%
Computational Efficiency
12%
Network Framework
12%
Virtual Monoenergetic Images
12%
Energy Dependence
12%
Monoenergetic Images
12%
Physics-based Method
12%
Parametric Maps
12%
Nonlinear Mapping
12%
Bone Fats
12%
Image Pair
12%
Training Targets
12%
Energy Approach
12%
Cycle-consistent Adversarial Network
12%
Residual Block
12%
Map Accuracy
12%
Head-and-neck
12%
Computer Science
Map Estimation
100%
Mean Absolute Error
100%
Deep Convolutional Neural Networks
100%
Cancer Patient
50%
Clinical Application
50%
Image Quality
50%
Image Noise
50%
Computational Efficiency
50%
Generative Adversarial Networks
50%
Deep Learning Model
50%
Nonlinear Mapping
50%
Subsequent Processing
50%
Deep Learning Method
50%
Engineering
Stopping Power
100%
Power Map
100%
Map Estimation
100%
Convolutional Neural Network
100%
Mean Absolute Error
25%
Noise Level
12%
Image Noise
12%
Clinical Application
12%
Computational Efficiency
12%
Image Pair
12%
Deep Learning Method
12%
Generative Adversarial Networks
12%
Deep Learning Model
12%
Physics
Stopping Power
100%
Convolutional Neural Network
100%
Physics
37%
Deep Learning Method
25%
Photoelectricity
12%
Head and Neck Cancer
12%
Lung
12%