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A nonlinear lag correction algorithm for a-Si flat-panel x-ray detectors

机译:a-Si平板x射线探测器的非线性滞后校正算法

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摘要

>Purpose: Detector lag, or residual signal, in a-Si flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and correct lag by deconvolution with an impulse response function (IRF). However, the lag correction is sensitive to both the exposure intensity and the technique used for determining the IRF. Even when the LTI correction that produces the minimum error is found, residual artifact remains. A new non-LTI method was developed to take into account the IRF measurement technique and exposure dependencies.>Methods: First, a multiexponential (N = 4) LTI model was implemented for lag correction. Next, a non-LTI lag correction, known as the nonlinear consistent stored charge (NLCSC) method, was developed based on the LTI multiexponential method. It differs from other nonlinear lag correction algorithms in that it maintains a consistent estimate of the amount of charge stored in the FP and it does not require intimate knowledge of the semiconductor parameters specific to the FP. For the NLCSC method, all coefficients of the IRF are functions of exposure intensity. Another nonlinear lag correction method that only used an intensity weighting of the IRF was also compared. The correction algorithms were applied to step-response projection data and CT acquisitions of a large pelvic phantom and an acrylic head phantom. The authors collected rising and falling edge step-response data on a Varian 4030CB a-Si FP detector operating in dynamic gain mode at 15 fps at nine incident exposures (2.0%–92% of the detector saturation exposure). For projection data, 1st and 50th frame lag were measured before and after correction. For the CT reconstructions, five pairs of ROIs were defined and the maximum and mean signal differences within a pair were calculated for the different exposures and step-response edge techniques.>Results: The LTI corrections left residual 1st and 50th frame lag up to 1.4% and 0.48%, while the NLCSC lag correction reduced 1st and 50th frame residual lags to less than 0.29% and 0.0052%. For CT reconstructions, the NLCSC lag correction gave an average error of 11 HU for the pelvic phantom and 3 HU for the head phantom, compared to 14–19 HU and 2–11 HU for the LTI corrections and 15 HU and 9 HU for the intensity weighted non-LTI algorithm. The maximum ROI error was always smallest for the NLCSC correction. The NLCSC correction was also superior to the intensity weighting algorithm.>Conclusions: The NLCSC lag algorithm corrected for the exposure dependence of lag, provided superior image improvement for the pelvic phantom reconstruction, and gave similar results to the best case LTI results for the head phantom. The blurred ring artifact that is left over in the LTI corrections was better removed by the NLCSC correction in all cases.
机译:>目的:a-Si平板(FP)检测器中的检测器滞后或残留信号会在锥束计算机X线断层扫描重建过程中引起明显的阴影伪影。迄今为止,大多数校正模型都采用线性时不变(LTI)模型,并通过使用脉冲响应函数(IRF)进行反卷积来校正滞后。但是,滞后校正对曝光强度和用于确定IRF的技术都敏感。即使找到产生最小误差的LTI校正,仍会残留残余伪像。考虑到IRF测量技术和曝光依赖性,开发了一种新的非LTI方法。>方法:首先,实现了一个多指数(N = 4)LTI模型用于滞后校正。接下来,基于LTI多指数方法,开发了一种非LTI滞后校正方法,称为非线性一致存储电荷(NLCSC)方法。它与其他非线性滞后校正算法的不同之处在于,它对FP中存储的电荷量保持一致的估计,并且不需要熟悉FP特定的半导体参数。对于NLCSC方法,IRF的所有系数都是曝光强度的函数。还比较了另一种仅使用IRF强度加权的非线性滞后校正方法。校正算法应用于大型骨盆模型和丙烯酸头部模型的阶跃响应投影数据和CT采集。作者收集了Varian 4030CB a-Si FP探测器的上升沿和下降沿阶跃响应数据,该探测器在9次入射曝光(探测器饱和曝光的2.0%–92%)下以15 fps的动态增益模式工作。对于投影数据,在校正前后分别测量第1帧和第50帧的延迟。对于CT重建,定义了五对ROI,并针对不同的曝光和阶跃响应边缘技术计算了一对中的最大和平均信号差。>结果: LTI校正保留了第一和第二残留第50帧时滞分别达到1.4%和0.48%,而NLCSC时滞校正将第1帧和第50帧时滞降低到0.29%和0.0052%以下。对于CT重建,NLCSC滞后校正的盆腔体模平均误差为11 HU,头部体模的平均误差为3 HU,而LTI校正的平均误差为14–19 HU和2–11 HU,而LTI校正的平均误差为15 HU和9 HU。强度加权非LTI算法。对于NLCSC校正,最大的ROI误差始终最小。 NLCSC校正也优于强度加权算法。>结论: NLCSC滞后算法校正了滞后的曝光依赖性,为盆腔体模重建提供了出色的图像改进,并且给出了相似的结果,最好情况LTI导致幻影。在所有情况下,通过NLCSC校正可以更好地消除LTI校正中遗留的模糊环伪影。

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