title: Minimum cross-entropy reconstruction of PET images with anatomically based anisotropic median-diffusion filtering.
abstract: We propose a spatially-variant anisotropic median-diffusion filter prior aided by anatomical knowledge for PET reconstruction. The anisotropic median-diffusion filter is applied locally to an anatomical region which is defined from a co-registered CT image. The individually smoothed regions are then combined to form a prior term in the minimum cross-entropy reconstruction algorithm. A simulated PET thorax phantom with lesions was investigated in terms of bias and contrast versus noise tradeoffs. Compared with MLEM and three other maximum a posteriori (MAP)-like reconstruction algorithms, the proposed algorithm demonstrated better bias-noise tradeoff except when the lesion was close to an anatomical boundary and better contrast-noise tradeoff in all cases.
authors.affiliation: Biomedical & Multimedia Information Technology (BMIT) Research Group, School of Information Technologies, University of Sydney, Australia.
authors.forename: Chung
authors.initials: C
authors.lastname: Chan
authors.forename: Roger
authors.initials: R
authors.lastname: Fulton
authors.forename: Weidong
authors.initials: W
authors.lastname: Cai
authors.forename: David Dagan
authors.initials: DD
authors.lastname: Feng
authors.forename: Steven
authors.initials: S
authors.lastname: Meikle
mesh_terms: D000465:Algorithms; D016880:Anisotropy; D007091:Image Processing, Computer-Assisted; D049268:Positron-Emission Tomography; D013909:Thorax