Quantitative evaluation of deep convolutional neural network-based image denoising for low-dose computed tomography

Abstract To minimize radiation risk, dose reduction is important in the diagnostic and therapeutic applications of computed tomography (CT). However, image noise degrades image quality owing to the reduced X-ray dose and a possible unacceptably reduced diagnostic performance. Deep learning approache...

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Principais autores:	Keisuke Usui, Koichi Ogawa, Masami Goto, Yasuaki Sakano, Shinsuke Kyougoku, Hiroyuki Daida
Formato:	Artigo
Idioma:	Inglês
Publicado em:	SpringerOpen 2021-07-01
coleção:	Visual Computing for Industry, Biomedicine, and Art
Assuntos:	Deep learning Convolutional neural network Low-dose computed tomography Denoising Image quality
Acesso em linha:	https://doi.org/10.1186/s42492-021-00087-9
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