Low-dose CT denoising with convolutional neural network Article Swipe

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

YOU? · · 2016 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1610.00321

To reduce the potential radiation risk, low-dose CT has attracted much attention. However, simply lowering the radiation dose will lead to significant deterioration of the image quality. In this paper, we propose a noise reduction method for low-dose CT via deep neural network without accessing original projection data. A deep convolutional neural network is trained to transform low-dose CT images towards normal-dose CT images, patch by patch. Visual and quantitative evaluation demonstrates a competing performance of the proposed method.

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Convolutional Neural Network

Artificial Intelligence

Concepts

Convolutional neural network Noise reduction Artificial intelligence Computer science Radiation dose Image quality Projection (relational algebra) Noise (video) Pattern recognition (psychology) Image denoising Reduction (mathematics) Artificial neural network Computer vision Image (mathematics) Nuclear medicine Medicine Mathematics Algorithm Geometry

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/1610.00321
PDF: https://arxiv.org/pdf/1610.00321
OA Status: green
Cited By: 8
Related Works: 10
OpenAlex ID: https://openalex.org/W2953230602

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DOI: https://doi.org/10.48550/arxiv.1610.00321

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Title: Low-dose CT denoising with convolutional neural network

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Type: preprint

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Language: en

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Publication year: 2016

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Publication date: 2016-10-02

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Authors: Hu Chen, Yi Zhang, Weihua Zhang, Peixi Liao, Ke Li, Jiliu Zhou, Ge Wang

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Landing page: https://arxiv.org/abs/1610.00321

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PDF URL: https://arxiv.org/pdf/1610.00321

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Concepts: Convolutional neural network, Noise reduction, Artificial intelligence, Computer science, Radiation dose, Image quality, Projection (relational algebra), Noise (video), Pattern recognition (psychology), Image denoising, Reduction (mathematics), Artificial neural network, Computer vision, Image (mathematics), Nuclear medicine, Medicine, Mathematics, Algorithm, Geometry

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Cited by: 8

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Citations by year (recent): 2020: 2, 2019: 3, 2018: 1, 2017: 1, 2016: 1

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Related works (count): 10

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