Abstract: JBFnet - Low Dose CT-denoising by Trainable Joint Bilateral Filtering.

Published on Jan 1, 2021
Mayank Patwari2
Estimated H-index: 2
,
Ralf Gutjahr7
Estimated H-index: 7
+ 1 AuthorsAndreas Maier39
Estimated H-index: 39
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#1Mayank Patwari (Siemens)H-Index: 2
#2Ralf Gutjahr (Siemens)H-Index: 7
Last. Rainer Raupach (Siemens)H-Index: 31
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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 bilateral filtering. The filter functions of the Joint Bi...
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