HybridFormer: a convolutional neural network-Transformer architecture for low dose computed tomography image denoising

HybridFormer: a convolutional neural network-Transformer architecture for low dose computed tomography image denoising

Low-dose computed tomography (CT) is a potent strategy to minimize X-ray radiation and its detrimental effects on patients. However, reducing radiation significantly boosts noise in reconstructed images, causing blur and obscuring critical tissue details. This obscurity poses significant challenges...

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Bibliographic Details
Main Authors: Shanaz Sharmin Jui, Zhitao Guo, Rending Jiang, Jiale Liu, Bohua Li
Format: Article
Language:English
Published: PeerJ Inc. 2025-07-01
Series:PeerJ Computer Science
Subjects:
Low-dose CT
Deep learning
CT image denoising
Transformer
Online Access:https://peerj.com/articles/cs-2952.pdf
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https://peerj.com/articles/cs-2952.pdf

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