Tward Daniel J, Siewerdsen Jeffrey H
Ontario Cancer Institute, Princess Margaret Hospital, Toronto, Ontario, Canada.
Med Phys. 2008 Dec;35(12):5510-29. doi: 10.1118/1.3002414.
The physical factors that govern 2D and 3D imaging performance may be understood from quantitative analysis of the spatial-frequency-dependent signal and noise transfer characteristics [e.g., modulation transfer function (MTF), noise-power spectrum (NPS), detective quantum efficiency (DQE), and noise-equivalent quanta (NEQ)] along with a task-based assessment of performance (e.g., detectability index). This paper advances a theoretical framework based on cascaded systems analysis for calculation of such metrics in cone-beam CT (CBCT). The model considers the 2D projection NPS propagated through a series of reconstruction stages to yield the 3D NPS and allows quantitative investigation of tradeoffs in image quality associated with acquisition and reconstruction techniques. While the mathematical process of 3D image reconstruction is deterministic, it is shown that the process is irreversible, the associated reconstruction parameters significantly affect the 3D DQE and NEQ, and system optimization should consider the full 3D imaging chain. Factors considered in the cascade include: system geometry; number of projection views; logarithmic scaling; ramp, apodization, and interpolation filters; 3D back-projection; and 3D sampling (noise aliasing). The model is validated in comparison to experiment across a broad range of dose, reconstruction filters, and voxel sizes, and the effects of 3D noise correlation on detectability are explored. The work presents a model for the 3D NPS, DQE, and NEQ of CBCT that reduces to conventional descriptions of axial CT as a special case and provides a fairly general framework that can be applied to the design and optimization of CBCT systems for various applications.
通过对空间频率相关的信号和噪声传递特性[例如,调制传递函数(MTF)、噪声功率谱(NPS)、探测量子效率(DQE)和噪声等效量子(NEQ)]进行定量分析,并结合基于任务的性能评估(例如,可探测性指数),可以理解控制二维和三维成像性能的物理因素。本文提出了一个基于级联系统分析的理论框架,用于计算锥束CT(CBCT)中的此类指标。该模型考虑了二维投影NPS通过一系列重建阶段传播以产生三维NPS,并允许对与采集和重建技术相关的图像质量权衡进行定量研究。虽然三维图像重建的数学过程是确定性的,但结果表明该过程是不可逆的,相关的重建参数会显著影响三维DQE和NEQ,并且系统优化应考虑整个三维成像链。级联中考虑的因素包括:系统几何形状;投影视图数量;对数缩放;斜坡、变迹和插值滤波器;三维反投影;以及三维采样(噪声混叠)。该模型在广泛的剂量、重建滤波器和体素尺寸范围内与实验进行了比较验证,并探讨了三维噪声相关性对可探测性的影响。这项工作提出了一个用于CBCT的三维NPS、DQE和NEQ的模型,该模型在特殊情况下简化为轴向CT的传统描述,并提供了一个相当通用的框架,可应用于各种应用的CBCT系统的设计和优化。