Hformer: highly efficient vision transformer for low-dose CT denoising

In this paper, we propose Hformer, a novel supervised learning model for low-dose computer tomography (LDCT) denoising. Hformer combines the strengths of convolutional neural networks for local feature extraction and transformer models for global feature capture. The performance of Hformer was verif...

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Veröffentlicht in:	Nuclear science and techniques 2023-04, Vol.34 (4), p.161-174, Article 61
Hauptverfasser:	Zhang, Shi-Yu, Wang, Zhao-Xuan, Yang, Hai-Bo, Chen, Yi-Lun, Li, Yang, Pan, Quan, Wang, Hong-Kai, Zhao, Cheng-Xin
Format:	Artikel
Sprache:	eng
Schlagworte:	Beam Physics Nuclear Energy Particle Acceleration and Detection Particle and Nuclear Physics Physics Physics and Astronomy
Online-Zugang:	Volltext
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