A Dual-Encoder-Single-Decoder Based Low-Dose CT Denoising Network

Generative adversarial networks (GAN) have shown great potential for image quality improvement in low-dose CT (LDCT). In general, the shallow features of generator include more shallow visual information such as edges and texture, while the deep features of generator contain more deep semantic infor...

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Veröffentlicht in:	IEEE journal of biomedical and health informatics Jg. 26; H. 7; S. 3251 - 3260
Hauptverfasser:	Han, Zefang, Shangguan, Hong, Zhang, Xiong, Zhang, Pengcheng, Cui, Xueying, Ren, Huiying
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.07.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Bioinformatics Coders Complementation Computed tomography Encoder-decoder structure Feature extraction Generative adversarial network Generative adversarial networks hierarchical-split ResNet image denoising Image edge detection Image quality LDCT Medical imaging Modules Noise reduction Quality control Redundancy Self-similarity Semantics Structural hierarchy Testing X-ray imaging
ISSN:	2168-2194, 2168-2208, 2168-2208
Online-Zugang:	Volltext
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