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Segmentation-Free X-ray Energy Spectrum Estimation for Computed Tomography Using Dual-Energy Material Decomposition

机译:计算机无分割X射线能谱估计   使用双能量材料分解的层析成像

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摘要

X-ray energy spectrum plays an essential role in computed tomography (CT)imaging and related tasks. Due to the high photon flux of clinical CT scanners,most of spectrum estimation methods are indirect and usually suffered fromvarious limitations. In this study, we aim to provide a segmentation-freeindirect transmission measurement-based energy spectrum estimation method usingdual-energy material decomposition. The general principle of the method is tominimize the quadratic error between the polychromatic forward projection andthe raw projection to calibrate a set of unknown weights which are used toexpress the unknown spectrum together with a set of model spectra. Thepolychromatic forward projection is performed using material-specific imageswhich are obtained using dual-energy material decomposition. The algorithm hasbeen evaluated using numerical simulations, experimental phantom data as wellas realistic patient data. The results show the estimated spectrum matches thereference spectrum quite well and the method is robust. Extensive studiessuggest the method provides accurate estimate of the CT spectrum withoutdedicated physical phantom and prolonged work flow. This paper may beattractive for CT dose calculations, artifacts reduction, polychromatic imagereconstruction and other spectrum-involved CT applications.
机译:X射线能谱在计算机断层扫描(CT)成像和相关任务中起着至关重要的作用。由于临床CT扫描仪的高光子通量,大多数光谱估计方法都是间接的,通常会受到各种限制。在这项研究中,我们旨在提供一种基于双能量材料分解的基于无分段间接传输测量的能谱估计方法。该方法的一般原理是最小化多色正向投影和原始投影之间的二次误差,以校准一组未知权重,该权重用于表达未知光谱以及一组模型光谱。多色正投影是使用特定材料的图像执行的,该特定材料的图像是使用双能材料分解获得的。该算法已使用数值模拟,实验体模数据以及实际患者数据进行了评估。结果表明,所估计的光谱与参考光谱非常匹配,并且该方法是鲁棒的。大量的研究表明,该方法可以准确估算CT频谱,而无需专用的体模和延长的工作流程。本文对于CT剂量计算,减少伪影,多色图像重建和其他涉及光谱的CT应用可能具有吸引力。

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