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Noise Reduction in Brain CT: A Comparative Study of Deep Learning and Hybrid Iterative Reconstruction Using Multiple Parameters

Objectives: We evaluated the noise reduction effects of deep learning reconstruction (DLR) and hybrid iterative reconstruction (HIR) in brain computed tomography (CT). Methods: CT images of a 16 cm dosimetry phantom, a head phantom, and the brains of 11 patients were reconstructed using filtered bac...

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Huvudupphov: Yusuke Inoue, Hiroyasu Itoh, Hirofumi Hata, Hiroki Miyatake, Kohei Mitsui, Shunichi Uehara, Chisaki Masuda
Materialtyp: Artigo
Språk:Inglês
Utgiven: MDPI AG 2024-12-01
Serie:Tomography
Ämnen:
computed tomography
brain
deep learning reconstruction
hybrid iterative reconstruction
image noise
Länkar:https://www.mdpi.com/2379-139X/10/12/147
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