On the 2D Fan-beam CT Reconstruction from Insufficient Projection Data
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摘要: 在医学和其他的很多CT应用中,一个重要问题是如何从不充分的投影数据中重建出断层图像。近年来由于新兴的压缩传感理论,Total Variation最小化方法在求解这一问题中重新获得了重视。本文将该方法推广成一类更一般的不充分投影CT重建算法。这一类重建算法同样基于压缩传感理论,但是更加灵活,能适用于不同的应用背景。针对该类算法中的一个特例进行的理论分析和算法仿真展现了该算法的应用潜力。Abstract: CT reconstruction from insufficient data is important in many medical and other applications.Recently to solve this under-determined problem,the Total Variation minimization method has regained popularity due to the newly-emerging compressed sensing theory.In this paper TV-minimization is extended to a more general framework for CT reconstuction from insufficient data.The framework proposed is also based on the compressed sensing theory,but is more flexible and amenable to various applications.Analysis and simulations are conducted for an initial special case and promising results are achieved.
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