Model-based iterative reconstruction for flat-panel cone-beam CT with focal spot blur, detector blur, and correlated noise.

Model-based iterative reconstruction for flat-panel cone-beam CT with focal spot blur, detector blur, and correlated noise.
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DOI:
10.1088/0031-9155/61/1/296
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发表时间:
2016-01-07
影响因子:
3.5
通讯作者:
Stayman JW
Stayman JW
中科院分区:
工程技术2区
文献类型:
--
作者:
Tilley S;Siewerdsen JH;Stayman JW

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虽然基于模型的重建方法已成功应用于平板锥束CT(FP-CBCT)系统,但典型的实现忽略了投影数据中的空间相关性以及由于X射线源中的检测器和焦斑而引起的系统模糊。在这项工作中,我们开发了一个基于平板的系统的前向模型,该模型包括与有限焦斑尺寸和间接检测器(例如,闪烁体)。该前向模型用于开发分阶段重建框架,其中投影数据被去卷积和对数变换,然后是广义最小二乘重建,该重建利用非对角统计加权来解释采集和数据产生的相关性处理链。我们研究了这种新的重建方法在模拟数据和CBCT测试台数据的性能。与忽略噪声相关性的传统滤波反投影和基于模型的方法相比,所提出的方法产生了上级噪声分辨率折衷。例如,对于具有0.34 mm FWHM闪烁体模糊和0.70 FWHM焦斑模糊的系统,使用相关噪声模型而不是不相关噪声模型将分辨率提高了42%(方差匹配为6.9 × 10−8 mm−2)。虽然这一优点适用于具有不同模糊特性的各种系统,但对于源模糊大于检测器模糊的系统,改进最大。
While model-based reconstruction methods have been successfully applied to flat-panel cone-beam CT (FP-CBCT) systems, typical implementations ignore both spatial correlations in the projection data as well as system blurs due to the detector and focal spot in the x-ray source. In this work, we develop a forward model for flat-panel-based systems that includes blur and noise correlation associated with finite focal spot size and an indirect detector (e.g., scintillator). This forward model is used to develop a staged reconstruction framework where projection data are deconvolved and log-transformed, followed by a generalized least-squares reconstruction that utilizes a non-diagonal statistical weighting to account for the correlation that arises from the acquisition and data processing chain. We investigate the performance of this novel reconstruction approach in both simulated data and in CBCT test-bench data. In comparison to traditional filtered backprojection and model-based methods that ignore noise correlation, the proposed approach yields a superior noise-resolution tradeoff. For example, for a system with 0.34 mm FWHM scintillator blur and 0.70 FWHM focal spot blur, using the a correlated noise model instead of an uncorrelated noise model increased resolution by 42% (with variance matched at 6.9 × 10−8 mm−2). While this advantage holds across a wide range of systems with differing blur characteristics, the improvements are greatest for systems where source blur is larger than detector blur.
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