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Neural KEM: A Kernel Method with Deep Coefficient Prior for PET Image Reconstruction
In this paper, we propose an implicit regularization for the kernel method by using a deep coefficient prior, which represents the kernel coefficient image in the PET forward model using a convolutional neural-network.
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