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LEARN++: Recurrent Dual-Domain Reconstruction Network for Compressed Sensing CT
Compressed sensing (CS) computed tomography has been proven to be import...
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Fourth-Order Nonlocal Tensor Decomposition Model for Spectral Computed Tomography
Spectral computed tomography (CT) can reconstruct spectral images from d...
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CT Reconstruction with PDF: Parameter-Dependent Framework for Multiple Scanning Geometries and Dose Levels
Current mainstream of CT reconstruction methods based on deep learning u...
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Learning Invariant Representation for Unsupervised Image Restoration
Recently, cross domain transfer has been applied for unsupervised image ...
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Visual Attention Network for Low Dose CT
Noise and artifacts are intrinsic to low dose CT (LDCT) data acquisition...
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Denoising of 3-D Magnetic Resonance Images Using a Residual Encoder-Decoder Wasserstein Generative Adversarial Network
Structure-preserved denoising of 3-D magnetic resonance images (MRI) is ...
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Learned Experts' Assessment-based Reconstruction Network ("LEARN") for Sparse-data CT
Compressive sensing (CS) has proved effective for tomographic reconstruc...
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Effective face landmark localization via single deep network
In this paper, we propose a novel face alignment method using single dee...
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Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)
Given the potential X-ray radiation risk to the patient, low-dose CT has...
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Low-dose CT denoising with convolutional neural network
To reduce the potential radiation risk, low-dose CT has attracted much a...
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