Deep Convolutional Neural Network for Inverse Problems in Imaging

In this paper, we propose a novel deep convolutional neural network (CNN)-based algorithm for solving ill-posed inverse problems. Regularized iterative algorithms have emerged as the standard approach to ill-posed inverse problems in the past few decades. These methods produce excellent results, but...

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Vydané v:	IEEE transactions on image processing Ročník 26; číslo 9; s. 4509 - 4522
Hlavní autori:	Jin, Kyong Hwan, McCann, Michael T., Froustey, Emmanuel, Unser, Michael
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.09.2017
Predmet:	biomedical imaging biomedical signal processing Computed tomography Convolution Image reconstruction Image restoration Inverse problems Iterative methods magnetic resonance imaging Neural networks reconstruction algorithms tomography
ISSN:	1057-7149, 1941-0042, 1941-0042
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