Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies.

In recent years, X-ray low-dose computed tomography (LDCT) has garnered widespread attention due to its significant reduction in the risk of patient radiation exposure. However, LDCT images often contain a substantial amount of noises, adversely affecting diagnostic quality. To mitigate this, a plet...

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Bibliographic Details

Published in:	Journal of Imaging Informatics in Medicine Vol. 38; no. 2; pp. 902 - 931
Main Authors:	Zhao, Feixiang, Liu, Mingzhe, Xiang, Mingrong, Li, Dongfen, Jiang, Xin, Jin, Xiance, Lin, Cai, Wang, Ruili
Format:	algorithm diagnostic images equations & formulas pictorial review tables/charts Journal Article
Published:	Springer Nature Apr2025
Online Access:	View this record in EBSCOhost