Comput. Biol. Med. - Reconstruction of sparse-view X-ray computed tomography using adaptive iterative algorithms.

Tópicos

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Resumo

In this paper, we propose two reconstruction algorithms for sparse-view X-ray computed tomography (CT). Treating the reconstruction problems as data fidelity constrained total variation (TV) minimization, both algorithms adapt the alternate two-stage strategy: projection onto convex sets (POCS) for data fidelity and non-negativity constraints and steepest descent for TV minimization. The novelty of this work is to determine iterative parameters automatically from data, thus avoiding tedious manual parameter tuning. In TV minimization, the step sizes of steepest descent are adaptively adjusted according to the difference from POCS update in either the projection domain or the image domain, while the step size of algebraic reconstruction technique (ART) in POCS is determined based on the data noise level. In addition, projection errors are used to compare with the error bound to decide whether to perform ART so as to reduce computational costs. The performance of the proposed methods is studied and evaluated using both simulated and physical phantom data. Our methods with automatic parameter tuning achieve similar, if not better, reconstruction performance compared to a representative two-stage algorithm.

Resumo Limpo

paper propos two reconstruct algorithm sparseview xray comput tomographi ct treat reconstruct problem data fidel constrain total variat tv minim algorithm adapt altern twostag strategi project onto convex set poc data fidel nonneg constraint steepest descent tv minim novelti work determin iter paramet automat data thus avoid tedious manual paramet tune tv minim step size steepest descent adapt adjust accord differ poc updat either project domain imag domain step size algebra reconstruct techniqu art poc determin base data nois level addit project error use compar error bound decid whether perform art reduc comput cost perform propos method studi evalu use simul physic phantom data method automat paramet tune achiev similar better reconstruct perform compar repres twostag algorithm

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