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Backprojection Wiener deconvolution for computed tomographic reconstruction
journal contribution
posted on 2018-12-21, 00:00 authored by Zhenglin WangZhenglin Wang, J Cai, Wanwu GuoWanwu Guo, M Donnelley, D Parsons, I LeeAnalytical CT reconstruction is popular in practice because of its computational efficiency, but it suffers from low reconstruction quality when an insufficient number of projections are used. To address this issue, this paper presents a new analytical method of backprojection Wiener deconvolution (BPWD). BPWD executes backprojection first, and then applies a Wiener deconvolution to the whole backprojected image. The Wiener filter is derived from a ramp filter, enabling the proposed approach to perform reconstruction and denoising simultaneously. The use of a filter after backprojection does not differentiate between real sampled projections and interpolated ones, introducing reconstruction errors. Therefore a weighted ramp filter was applied to increase the contribution of real sampled projections in the reconstruction, thus improving reconstruction quality. Experiments on synthetic data and real phase-contrast x-ray images showed that the proposed approach yields better reconstruction quality compared to the classical filtered backprojection (FBP) method, with comparable reconstruction speed.
History
Volume
13Issue
12Start Page
1End Page
22Number of Pages
22eISSN
1932-6203Publisher
Public Library of Science (PLoS)Publisher DOI
Additional Rights
CC BY 4.0Language
enPeer Reviewed
- Yes
Open Access
- Yes
Acceptance Date
2018-11-08External Author Affiliations
University of Adelaide; University of South Australia; 3 Respiratory and Sleep Medicine, Women’s and Children’s Hospital, North Adelaide, SA,Author Research Institute
- Centre for Intelligent Systems
Era Eligible
- Yes