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Objective assessment of image quality and dose reduction in CT iterative reconstruction

机译:CT迭代重建中图像质量和减少剂量的客观评估

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Purpose: Iterative reconstruction (IR) algorithms have the potential to reduce radiation dose in CT diagnostic imaging. As these algorithms become available on the market, a standardizable method of quantifying the dose reduction that a particular IR method can achieve would be valuable. Such a method would assist manufacturers in making promotional claims about dose reduction, buyers in comparing different devices, physicists in independently validating the claims, and the United States Food and Drug Administration in regulating the labeling of CT devices. However, the nonlinear nature of commercially available IR algorithms poses challenges to objectively assessing image quality, a necessary step in establishing the amount of dose reduction that a given IR algorithm can achieve without compromising that image quality. This review paper seeks to consolidate information relevant to objectively assessing the quality of CT IR images, and thereby measuring the level of dose reduction that a given IR algorithm can achieve.Methods: The authors discuss task-based methods for assessing the quality of CT IR images and evaluating dose reduction.Results: The authors explain and review recent literature on signal detection and localization tasks in CT IR image quality assessment, the design of an appropriate phantom for these tasks, possible choices of observers (including human and model observers), and methods of evaluating observer performance.Conclusions: Standardizing the measurement of dose reduction is a problem of broad interest to the CT community and to public health. A necessary step in the process is the objective assessment of CT image quality, for which various task-based methods may be suitable. This paper attempts to consolidate recent literature that is relevant to the development and implementation of task-based methods for the assessment of CT IR image quality.
机译:目的:迭代重建(IR)算法具有减少CT诊断成像中辐射剂量的潜力。随着这些算法在市场上的普及,一种量化特定IR方法可以实现的剂量减少的标准化方法将很有价值。这种方法将有助于制造商就减少剂量提出促销性声明,帮助购买者比较不同的设备,让物理学家独立地验证这些声明,并帮助美国食品药品管理局管理CT设备的标签。但是,市售IR算法的非线性特性给客观评估图像质量带来了挑战,这是确定给定IR算法在不影响图像质量的前提下可以实现的剂量减少量的必要步骤。这篇综述旨在寻求与客观评估CT IR图像质量有关的信息,从而衡量给定IR算法可以达到的剂量减少水平。方法:作者讨论了基于任务的评估CT IR质量的方法结果:作者解释并回顾了有关CT IR图像质量评估中信号检测和定位任务的最新文献,为这些任务设计了合适的体模,可能选择了观察者(包括人类和模型观察者),结论:降低剂量的标准化测量是CT界和公众健康广泛关注的问题。该过程中的必要步骤是对CT图像质量进行客观评估,为此,各种基于任务的方法可能适用。本文试图巩固与发展和实施基于任务的方法评估CT IR图像质量有关的最新文献。

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