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Evaluation of hardware in a small-animal SPECT system using reconstructed images

机译:使用重建图像评估小动物SPECT系统中的硬件

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摘要

Evaluation of imaging hardware represents a vital component of system design. In small-animal SPECT imaging, this evaluation has become increasingly difficult with the emergence of multi-pinhole apertures and adaptive, or patient-specific, imaging. This paper will describe two methods for hardware evaluation using reconstructed images. The first method is a rapid technique incorporating a system-specific non-linear, three-dimensional point response. This point response is easily computed and offers qualitative insight into an aperture’s resolution and artifact characteristics. The second method is an objective assessment of signal detection in lumpy backgrounds using the channelized Hotelling observer (CHO) with 3D Laguerre-Gauss and difference-of-Gaussian channels to calculate area under the receiver-operating characteristic curve (AUC). Previous work presented at this meeting described a unique, small-animal SPECT system (M3R) capable of operating under a myriad of hardware configurations and ideally suited for image quality studies. Measured system matrices were collected for several hardware configurations of M3R. The data used to implement these two methods was then generated by taking simulated objects through the measured system matrices. The results of these two methods comprise a combination of qualitative and quantitative analysis that is well-suited for hardware assessment.
机译:评估成像硬件是系统设计的重要组成部分。在小动物SPECT成像中,随着多针孔孔径和自适应成像或针对患者的成像的出现,这种评估变得越来越困难。本文将介绍两种使用重建图像进行硬件评估的方法。第一种方法是结合了系统特定的非线性三维点响应的快速技术。该点响应很容易计算,并且可以对光圈的分辨率和伪像特性进行定性分析。第二种方法是使用带有3D Laguerre-Gauss和高斯差分通道的信道化Hotelling观测器(CHO),对块状背景中的信号检测进行客观评估,以计算接收器工作特性曲线(AUC)下的面积。在这次会议上介绍的先前工作描述了一种独特的小动物SPECT系统(M 3 R),该系统能够在多种硬件配置下运行,非常适合图像质量研究。收集了M 3 R的几种硬件配置的测量系统矩阵。然后通过通过测量的系统矩阵获取模拟对象来生成用于实现这两种方法的数据。这两种方法的结果包括定性和定量分析的组合,非常适合硬件评估。

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