JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering

Pages: 506 - 515
Published: Jan 1, 2020
Abstract
Deep neural networks have shown great success in low dose CT denoising. However, most of these deep neural networks have several hundred thousand trainable parameters. This, combined with the inherent non-linearity of the neural network, makes the deep neural network diffcult to understand with low accountability. In this study we introduce JBFnet, a neural network for low dose CT denoising. The architecture of JBFnet implements iterative...
Paper Details
Title
JBFnet - Low Dose CT Denoising by Trainable Joint Bilateral Filtering
Published Date
Jan 1, 2020
Pages
506 - 515
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