title: Laplace operator based reconstruction algorithm for truncated spiral cone beam computed tomography.
abstract: To reconstruct images from truncated projections collected along a spiral trajectory, the most common approach is to smoothly extrapolate each projection to suppress truncation artifacts. Based on the work of Dennerlein, a local reconstruction algorithm is developed for spiral cone beam computed tomography (CT), which does not need explicit projection extrapolation. This algorithm is a filtered-backprojection (FBP) format and contains three major steps: cosine weight, filtration, and backprojection. While the cosine weight and backprojection steps are the same as the classical Feldkamp - Davis - Kress (FDK) scheme, the filtering step contains two steps: Laplace filtering and Radon transform-based filtering. Numerical simulation results show that the proposed algorithm has a better performance than FDK algorithm for region-of-interest (ROI) reconstruction of spiral cone-beam CT.
authors.affiliation: Department of Mathematics and Information Engineering, Chongqing University of Education, Chongqing, China.
authors.forename: Xiaobing
authors.initials: X
authors.lastname: Zou
authors.forename: Hengyong
authors.initials: H
authors.lastname: Yu
authors.forename: Li
authors.initials: L
authors.lastname: Zeng
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D021621:Imaging, Three-Dimensional; D019047:Phantoms, Imaging; D059629:Signal-To-Noise Ratio; D054894:Spiral Cone-Beam Computed Tomography / Q000379:methods*
keywords: Computed tomography; Laplace operator; local filtration; region-of-interest reconstruction; spiral cone beam computed tomography; truncated projection