光子衰减对SPECT成像中肿瘤-背景和信噪比的影响。

Edward J Soares, Michael A King, Charles L Byrne, Howard C Gifford, Andre Lehovich
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引用次数: 0

摘要

Nuyts等人[1],Bai等人[2],Bai和Shao[3]研究了衰减和衰减校正对肿瘤与背景比和信号检测的影响,在此基础上,我们推导出了用线性非迭代重建算子O重建的SPECT衰减数据的肿瘤与背景比(TBR)的一般表达式。这种情况的特殊情况是O表示离散滤波后的反投影(FBP)。重建的未校正的衰减数据的TBR(no-AC)可以写成FBP重建的未衰减数据的TBR(FBP)和FBP重建的“差”投影数据的TBR(diff)的加权和。我们评估了各种物体和衰减条件下TBR(no-AC)的表达式。在投影空间中计算理想观测器信噪比(SNR(理想)),以获得精确已知信号/精确已知背景(SKE/BKE)检测任务的信号可检测性上界。结果普遍表明,在衰减介质中较深处的肿瘤信噪比(理想信噪比)较低,而靠近物体边缘的肿瘤信噪比升高。均匀衰减系数μ越大,信噪比越低(理想值)。fbp重构、未校正的衰减数据的TBR可能会低估或高估真实TBR,这取决于衰减介质的几种特性,包括衰减器的形状、衰减器的均匀性和数据衰减的程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Influence of Photon Attenuation on Tumor-to-Background and Signal-to-Noise Ratios for SPECT Imaging.

Expanding on the work of Nuyts et. al [1], Bai et. al. [2], and Bai and Shao [3], who all studied the effects of attenuation and attenuation correction on tumor-to-background ratios and signal detection, we have derived a general expression for the tumor-to-background ratio (TBR) for SPECT attenuated data that have been reconstructed with a linear, non-iterative reconstruction operator O. A special case of this is when O represents discrete filtered back-projection (FBP). The TBR of the reconstructed, uncorrected attenuated data (TBR(no-AC)) can be written as a weighted sum of the TBR of the FBP-reconstructed unattenuated data (TBR(FBP)) and the TBR of the FBP-reconstructed "difference" projection data (TBR(diff)). We evaluated the expression for TBR(no-AC) for a variety of objects and attenuation conditions. The ideal observer signal-to-noise ratio (SNR(ideal)) was also computed in projection space, in order to obtain an upper bound on signal detectability for a signal-known-exactly/background-known-exactly (SKE/BKE) detection task. The results generally show that SNR(ideal) is lower for tumors located deeper within the attenuating medium and increases for tumors nearer the edge of the object. In addition, larger values for the uniform attenuation coefficient μ lead to lower values for SNR(ideal). The TBR for FBP-reconstructed, uncorrected attenuated data can both under- and over-estimate the true TBR, depending on several properties of the attenuating medium, including the shape of the attenuator, the uniformity of the attenuator, and the degree to which the data are attenuated.

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