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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Ngā kaituhi matua:	Yusuke Inoue, Hiroyasu Itoh, Hirofumi Hata, Hiroki Miyatake, Kohei Mitsui, Shunichi Uehara, Chisaki Masuda
Hōputu:	Artigo
Reo:	Inglês
I whakaputaina:	MDPI AG 2024-12-01
Rangatū:	Tomography
Ngā marau:	computed tomography brain deep learning reconstruction hybrid iterative reconstruction image noise
Urunga tuihono:	https://www.mdpi.com/2379-139X/10/12/147
Ngā Tūtohu:	Tāpirihia he Tūtohu Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!