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Assessing image quality and dose reduction of a new x-ray computed tomography iterative reconstruction algorithm using model observers

机译:使用模型观测器评估新的X射线计算机断层摄影迭代重建算法的图像质量和减少剂量

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Purpose: A number of different techniques have been developed to reduce radiation dose in x-ray computed tomography (CT) imaging. In this paper, the authors will compare task-based measures of image quality of CT images reconstructed by two algorithms: conventional filtered back projection (FBP), and a new iterative reconstruction algorithm (IR).Methods: To assess image quality, the authors used the performance of a channelized Hotelling observer acting on reconstructed image slices. The selected channels are dense difference Gaussian channels (DDOG). A body phantom and a head phantom were imaged 50 times at different dose levels to obtain the data needed to assess image quality. The phantoms consisted of uniform backgrounds with low contrast signals embedded at various locations. The tasks the observer model performed included (1) detection of a signal of known location and shape, and (2) detection and localization of a signal of known shape. The employed DDOG channels are based on the response of the human visual system. Performance was assessed using the areas under ROC curves and areas under localization ROC curves.Results: For signal known exactly (SKE) and location unknown/signal shape known tasks with circular signals of different sizes and contrasts, the authors' task-based measures showed that a FBP equivalent image quality can be achieved at lower dose levels using the IR algorithm. For the SKE case, the range of dose reduction is 50%-67% (head phantom) and 68%-82% (body phantom). For the study of location unknown/signal shape known, the dose reduction range can be reached at 67%-75% for head phantom and 67%-77% for body phantom case. These results suggest that the IR images at lower dose settings can reach the same image quality when compared to full dose conventional FBP images.Conclusions: The work presented provides an objective way to quantitatively assess the image quality of a newly introduced CT IR algorithm. The performance of the model observers using the IR images was always higher than that seen using the FBP images in the authors' SKE and SKE location unknown detection tasks. To achieve a FBP-equivalent image quality in CT systems, the authors can lower the radiation dose by using this IR image reconstruction algorithm. Further studies are warranted using clinical data and human observer to validate these results for more complicated and realistic tasks.
机译:目的:已经开发出许多不同的技术来减少X射线计算机断层扫描(CT)成像中的辐射剂量。在本文中,作者将比较通过两种算法重建的CT图像质量的基于任务的度量:传统的滤波反投影(FBP)和新的迭代重建算法(IR)。方法:为评估图像质量,作者运用了信道化的Hotelling观察者对重构图像切片的表现。所选通道为高斯密度差通道(DDOG)。人体模型和头部模型以不同的剂量水平成像50次,以获得评估图像质量所需的数据。幻像由均匀的背景组成,在不同位置嵌入了低对比度信号。观察者模型执行的任务包括(1)检测已知位置和形状的信号,以及(2)检测和定位已知形状的信号。使用的DDOG通道基于人类视觉系统的响应。通过使用ROC曲线下的区域和局部ROC曲线下的区域来评估性能。结果:对于具有不同大小和对比度的圆形信号的精确已知信号(SKE)和位置未知/信号形状已知任务,作者基于任务的度量表明使用IR算法可以在较低剂量水平上获得FBP等效图像质量。对于SKE病例,降低剂量的范围为50%-67%(头模)和68%-82%(体模)。对于未知位置/已知信号形状的研究,头部模型的剂量减少范围可以达到67%-75%,身体模型的剂量减少范围可以达到67%-77%。这些结果表明,与全剂量常规FBP图像相比,较低剂量设置下的IR图像可以达到相同的图像质量。结论:提出的工作为定量评估新引入的CT IR算法的图像质量提供了一种客观的方法。在作者的SKE和SKE位置未知检测任务中,使用IR图像的模型观察者的性能始终高于使用FBP图像看到的性能。为了在CT系统中达到FBP等效的图像质量,作者可以使用此IR图像重建算法降低辐射剂量。使用临床数据和观察者进行进一步的研究是必要的,以验证这些结果用于更复杂和现实的任务。

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