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Detector system comparison using relative CNR for specific imaging tasksrelated to neuro-endovascular image-guided interventions (neuro-EIGIs)

机译:使用相对CNR进行特定成像任务的探测器系统比较与神经血管内图像引导干预(neuro-EIGIs)有关

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摘要

Neuro-EIGIs require visualization of very small endovascular devices and small vessels. A Microangiographic Fluoroscope (MAF) x-ray detector was developed to improve on the standard flat panel detector’s (FPD’s) ability to visualize small objects during neuro-EIGIs. To compare the performance of FPD and MAF imaging systems, specific imaging tasks related to those encountered during neuro-EIGIs were used to assess contrast to noise ratio (CNR) of different objects. A bar phantom and a stent were placed at a fixed distance from the x-ray focal spot to mimic a clinical imaging geometry and both objects were imaged by each detector system. Imaging was done without anti-scatter grids and using the same conditions for each system including: the same x-ray beam quality, collimator position, source to imager distance (SID), and source to object distance (SOD). For each object, relative contrasts were found for both imaging systems using the peak and trough signals. The relative noise was found using mean background signal and background noise for varying detector exposures. Next, the CNRs were found for these values for each object imaged and for each imaging system used. A relative CNR metric is defined and used to compare detector imaging performance. The MAF utilizes a temporal filter to reduce the overall image noise. The effects of using this filter with the MAF while imaging the clinical object’s CNRs are reported. The relative CNRfor the detectors demonstrated that the MAF has superior CNRs for most objects andexposures investigated for this specific imaging task.
机译:神经EIGIs需要可视化非常小的血管内装置和小血管。开发了一种微血管荧光镜(MAF)X射线检测器,以提高标准平板检测器(FPD)在神经EIGI期间可视化小物体的能力。为了比较FPD和MAF成像系统的性能,将与神经EIGI期间遇到的任务相关的特定成像任务用于评估不同对象的对比噪声比(CNR)。将条状幻影和支架放置在距X射线焦点固定距离的位置,以模仿临床成像几何形状,并且两个物体都由每个探测器系统成像。成像是在没有防散射网格的情况下进行的,并且每个系统使用相同的条件,包括:相同的X射线束质量,准直仪位置,源到成像器的距离(SID)和源到物的距离(SOD)。对于每个物体,使用峰值和谷值信号在两个成像系统中都发现了相对对比度。使用平均背景信号和背景噪声来发现相对噪声,以用于变化的检测器曝光。接下来,针对每个成像对象和所使用的每个成像系统,为这些值找到CNR。定义了一个相对CNR度量,并将其用于比较检测器成像性能。 MAF利用时间滤波器来减少整体图像噪声。据报道,在对临床对象的CNR进行成像时,结合使用该滤镜和MAF会产生效果。相对CNR用于检测器的证明了MAF对于大多数物体具有出色的CNR针对此特定成像任务调查了曝光。

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