Comput. Biol. Med. - Sparse angular CT reconstruction using non-local means based iterative-correction POCS.

Tópicos

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Resumo

In divergent-beam computed tomography (CT), sparse angular sampling frequently leads to conspicuous streak artifacts. In this paper, we propose a novel non-local means (NL-means) based iterative-correction projection onto convex sets (POCS) algorithm, named as NLMIC-POCS, for effective and robust sparse angular CT reconstruction. The motivation for using NLMIC-POCS is that NL-means filtered image can produce an acceptable priori solution for sequential POCS iterative reconstruction. The NLMIC-POCS algorithm has been tested on simulated and real phantom data. The experimental results show that the presented NLMIC-POCS algorithm can significantly improve the image quality of the sparse angular CT reconstruction in suppressing streak artifacts and preserving the edges of the image.

Resumo Limpo

divergentbeam comput tomographi ct spars angular sampl frequent lead conspicu streak artifact paper propos novel nonloc mean nlmean base iterativecorrect project onto convex set poc algorithm name nlmicpoc effect robust spars angular ct reconstruct motiv use nlmicpoc nlmean filter imag can produc accept priori solut sequenti poc iter reconstruct nlmicpoc algorithm test simul real phantom data experiment result show present nlmicpoc algorithm can signific improv imag qualiti spars angular ct reconstruct suppress streak artifact preserv edg imag

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