Deep Encoder-Decoder Adversarial Reconstruction (DEAR) Network for 3D CT from Few-View Data

X-ray computed tomography (CT) is widely used in clinical practice. The involved ionizing X-ray radiation, however, could increase cancer risk. Hence, the reduction of the radiation dose has been an important topic in recent years. Few-view CT image reconstruction is one of the main ways to minimize...

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Vydané v:	Bioengineering (Basel) Ročník 6; číslo 4; s. 111
Hlavní autori:	Xie, Huidong, Shan, Hongming, Wang, Ge
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Switzerland MDPI AG 09.12.2019 MDPI
Predmet:	Algorithms Big Data Bioengineering Coders Computed tomography Datasets Deep learning Design Encoders-Decoders Image processing Image quality Image reconstruction Information processing Ionizing radiation Lung cancer Medical imaging Medical screening Methods Radiation Radiation dosage Tomography X-rays few-view CT deep learning generative adversarial network (GAN) machine learning deep encoder-decoder adversarial network (DEAR) sparse-view CT
ISSN:	2306-5354, 2306-5354
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