使用光子处理和光子计数单光子发射计算机断层扫描成像系统估计ROI活度浓度。
Estimating ROI activity concentration with photon-processing and photon-counting SPECT imaging systems.
作者信息
Jha Abhinav K, Frey Eric C
机构信息
Division of Medical Imaging Physics, Department of Radiology, Johns Hopkins University, Baltimore, MD, USA.
出版信息
Proc SPIE Int Soc Opt Eng. 2015 Apr 13;9412:94120R. doi: 10.1117/12.2082278.
Recently a new class of imaging systems, referred to as photon-processing (PP) systems, are being developed that uses real-time maximum-likelihood (ML) methods to estimate multiple attributes per detected photon and store these attributes in a list format. PP systems could have a number of potential advantages compared to systems that bin photons based on attributes such as energy, projection angle, and position, referred to as photon-counting (PC) systems. For example, PP systems do not suffer from binning-related information loss and provide the potential to extract information from attributes such as energy deposited by the detected photon. To quantify the effects of this advantage on task performance, objective evaluation studies are required. We performed this study in the context of quantitative 2-dimensional single-photon emission computed tomography (SPECT) imaging with the end task of estimating the mean activity concentration within a region of interest (ROI). We first theoretically outline the effect of null space on estimating the mean activity concentration, and argue that due to this effect, PP systems could have better estimation performance compared to PC systems with noise-free data. To evaluate the performance of PP and PC systems with noisy data, we developed a singular value decomposition (SVD)-based analytic method to estimate the activity concentration from PP systems. Using simulations, we studied the accuracy and precision of this technique in estimating the activity concentration. We used this framework to objectively compare PP and PC systems on the activity concentration estimation task. We investigated the effects of varying the size of the ROI and varying the number of bins for the attribute corresponding to the angular orientation of the detector in a continuously rotating SPECT system. The results indicate that in several cases, PP systems offer improved estimation performance compared to PC systems.
最近，一类被称为光子处理（PP）系统的新型成像系统正在被开发，它使用实时最大似然（ML）方法来估计每个检测到的光子的多个属性，并以列表形式存储这些属性。与基于能量、投影角度和位置等属性对光子进行分箱的系统（称为光子计数（PC）系统）相比，PP系统可能具有许多潜在优势。例如，PP系统不会遭受与分箱相关的信息损失，并提供了从检测到的光子沉积的能量等属性中提取信息的潜力。为了量化这一优势对任务性能的影响，需要进行客观评估研究。我们在定量二维单光子发射计算机断层扫描（SPECT）成像的背景下进行了这项研究，最终任务是估计感兴趣区域（ROI）内的平均活度浓度。我们首先从理论上概述了零空间对估计平均活度浓度的影响，并认为由于这种影响，与无噪声数据的PC系统相比，PP系统可能具有更好的估计性能。为了评估有噪声数据时PP和PC系统的性能，我们开发了一种基于奇异值分解（SVD）的解析方法来从PP系统估计活度浓度。通过模拟，我们研究了该技术在估计活度浓度方面的准确性和精度。我们使用这个框架在活度浓度估计任务上对PP和PC系统进行客观比较。我们研究了在连续旋转的SPECT系统中改变ROI大小和改变与探测器角向对应的属性的分箱数量的影响。结果表明，在几种情况下，PP系统与PC系统相比具有更好的估计性能。
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