EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising
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Updated
Apr 26, 2021 - Python
EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising
Sharpness-aware Low Dose CT Denoising Using Conditional Generative Adversarial Network
Framework for designing, training and benchmarking sparse-view CT reconstruction algorithms; includes datasets, metrics, baselines and CLI so you can prototype new methods and compare fairly in minutes.
Deep neural network for low-dose electron micrograph denoising
Github Code for "Noise-Generating and Imaging Mechanism Inspired Implicit Regularization Learning Network for Low Dose CT Reconstrution" (IEEE TMI 2024)
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