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arXiv · 1609.08508

Low-Dose CT via Deep Neural Network

Hu Chen·Yi Zhang·Weihua Zhang·Peixi Liao·Ke Li·Jiliu Zhou·Ge Wang
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Abstract

In order to reduce the potential radiation risk, low-dose CT has attracted more and more attention. However, simply lowering the radiation dose will significantly degrade the imaging quality. In this paper, we propose a noise reduction method for low-dose CT via deep learning without accessing the original projection data. An architecture of deep convolutional neural network was considered to map the low-dose CT images into its corresponding normal-dose CT images patch by patch. Qualitative and quantitative evaluations demonstrate a state-the-art performance of the proposed method.

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Hu Chen, Yi Zhang, Weihua Zhang, Peixi Liao, Ke Li, Jiliu Zhou, Ge Wang. 2016-09-27. Low-Dose CT via Deep Neural Network. https://arxiv.org/abs/1609.08508

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