TomoGC: Binary Tomography by Constrained GraphCuts

PATTERN RECOGNITION, GCPR 2015(2015)

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摘要
We present an iterative reconstruction algorithm for binary tomography, called TomoGC, that solves the reconstruction problem based on a constrained graphical model by a sequence of graphcuts. TomoGC reconstructs objects even if a low number of measurements are only given, which enables shorter observation periods and lower radiation doses in industrial and medical applications. We additionally suggest some modifications of established methods that improve state-of-the-art methods. A comprehensive numerical evaluation demonstrates that the proposed method can reconstruct objects from a small number of projections more accurate and also faster than competitive methods.
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关键词
Discrete Algebraic Reconstruction Technique (DART),Simultaneous Iterative Reconstruction Technique (SIRT),Discrete Tomography Problem,Spectral Projected Gradient (SPG),ASTRA Toolbox
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