title: Dynamic positron emission tomography image restoration via a kinetics-induced bilateral filter.
abstract: Dynamic positron emission tomography (PET) imaging is a powerful tool that provides useful quantitative information on physiological and biochemical processes. However, low signal-to-noise ratio in short dynamic frames makes accurate kinetic parameter estimation from noisy voxel-wise time activity curves (TAC) a challenging task. To address this problem, several spatial filters have been investigated to reduce the noise of each frame with noticeable gains. These filters include the Gaussian filter, bilateral filter, and wavelet-based filter. These filters usually consider only the local properties of each frame without exploring potential kinetic information from entire frames. Thus, in this work, to improve PET parametric imaging accuracy, we present a kinetics-induced bilateral filter (KIBF) to reduce the noise of dynamic image frames by incorporating the similarity between the voxel-wise TACs using the framework of bilateral filter. The aim of the proposed KIBF algorithm is to reduce the noise in homogeneous areas while preserving the distinct kinetics of regions of interest. Experimental results on digital brain phantom and in vivo rat study with typical (18)F-FDG kinetics have shown that the present KIBF algorithm can achieve notable gains over other existing algorithms in terms of quantitative accuracy measures and visual inspection.
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Zhaoying
authors.initials: Z
authors.lastname: Bian
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Jing
authors.initials: J
authors.lastname: Huang
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Ma
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Lijun
authors.initials: L
authors.lastname: Lu
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Shanzhou
authors.initials: S
authors.lastname: Niu
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Zeng
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Qianjin
authors.initials: Q
authors.lastname: Feng
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou, China.
authors.forename: Wufan
authors.initials: W
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000000981:diagnostic imaging; D005260:Female; D007091:Image Processing, Computer-Assisted; D007700:Kinetics; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000379:methods*; D051381:Rats; D059629:Signal-To-Noise Ratio