title: Dual-domain denoising in three dimensional magnetic resonance imaging.
abstract: Denoising is a crucial preprocessing procedure for three dimensional magnetic resonance imaging (3D MRI). Existing denoising methods are predominantly implemented in a single domain, ignoring information in other domains. However, denoising methods are becoming increasingly complex, making analysis and implementation challenging. The present study aimed to develop a dual-domain image denoising (DDID) algorithm for 3D MRI that encapsulates information from the spatial and transform domains. In the present study, the DDID method was used to distinguish signal from noise in the spatial and frequency domains, after which robust accurate noise estimation was introduced for iterative filtering, which is simple and beneficial for computation. In addition, the proposed method was compared quantitatively and qualitatively with existing methods for synthetic andin vivoMRI datasets. The results of the present study suggested that the novel DDID algorithm performed well and provided competitive results, as compared with existing MRI denoising filters.
authors.affiliation: Department of Computer Science, Chengdu University of Information Technology, Chengdu, Sichuan 610225, P.R. China.
authors.forename: Jing
authors.initials: J
authors.lastname: Peng
authors.affiliation: Department of Computer Science, Chengdu University of Information Technology, Chengdu, Sichuan 610225, P.R. China.
authors.forename: Jiliu
authors.initials: J
authors.lastname: Zhou
authors.affiliation: Department of Computer Science, Chengdu University of Information Technology, Chengdu, Sichuan 610225, P.R. China.
authors.forename: Xi
authors.initials: X
authors.lastname: Wu
keywords: dual-domain denoising; robust noise estimation; three dimensional magnetic resonance imaging denoising