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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...
12/13/2020 ∙ by Yi Zhang, et al. ∙
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Fourth-Order Nonlocal Tensor Decomposition Model for Spectral Computed Tomography
Spectral computed tomography (CT) can reconstruct spectral images from d...
10/27/2020 ∙ by Xiang Chen, et al. ∙
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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...
10/27/2020 ∙ by Wenjun Xia, et al. ∙
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Learning Invariant Representation for Unsupervised Image Restoration
Recently, cross domain transfer has been applied for unsupervised image ...
03/28/2020 ∙ by Wenchao Du, et al. ∙
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Visual Attention Network for Low Dose CT
Noise and artifacts are intrinsic to low dose CT (LDCT) data acquisition...
10/31/2018 ∙ by Wenchao Du, et al. ∙
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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 ...
08/12/2018 ∙ by Maosong Ran, et al. ∙
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Learned Experts' Assessment-based Reconstruction Network ("LEARN") for Sparse-data CT
Compressive sensing (CS) has proved effective for tomographic reconstruc...
07/30/2017 ∙ by Hu Chen, et al. ∙
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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...
02/09/2017 ∙ by Zongping Deng, et al. ∙
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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...
02/01/2017 ∙ by Hu Chen, et al. ∙
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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...
10/02/2016 ∙ by Hu Chen, et al. ∙
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