Error images for spectroscopic imaging by LCModel using Cramer-Rao bounds
Error images for spectroscopic imaging by LCModel using Cramer-Rao bounds
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DOI：
10.1007/s10334-005-0018-7
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发表时间：
2006-02-01
影响因子：
2.3
通讯作者：
Hajek, M
中科院分区：
文献类型：
--
作者：
Jiru, F;Skoch, A;Hajek, M
光谱成像 (SI) 测量的结果通常以代谢图像的形式呈现。如果光谱质量不够，计算出的浓度就会有偏差，并且代谢图像会显示不正确的代谢物分布。为了简化 SI 测量光谱的质量分析，反映计算浓度准确性的误差图像可以与代谢物图像一起显示。在本文中，使用光谱模拟验证了由 LCModel 程序计算的 Cramer-Rao 界限（CRB）与描述估计浓度误差的相关性。评估了不同信噪比和谱线展宽条件下 100 个模拟光谱的平均 CRB 和代谢物浓度标准差 (STD) 之间的关系。提出了计算代谢物比率误差图像的参数，并展示了显示误差图像的有效方法。结果表明，平均 CRB 与标准偏差密切相关，因此 CRB 值反映了计算浓度的相对不确定性。通过仅显示代谢物图像中相应的 CRB 低于选定阈值的那些区域，或者通过将 CRB 映射为代谢物图像的透明度，可以将误差信息直接集成到代谢物图像中。误差图像的概念避免了对每个 SI 光谱的广泛检查，并有助于拒绝低质量光谱。
The results of spectroscopic imaging (SI) measurements are often presented as metabolic images. If the spectra quality is not sufficient, the calculated concentrations are biased and the metabolic images show an incorrect metabolite distribution. To simplify the quality analysis of spectra measured by SI, an error image, reflecting the accuracy of the computed concentrations, can be displayed along with the metabolite image. In this paper the relevance of Cramer-Rao bounds (CRBs) calculated by the LCModel program to describe errors in estimated concentrations is validated using spectra simulations. The relation between the average CRBs and standard deviations (STD) of metabolite concentrations from 100 simulated spectra for various signal to noise ratio and line broadening conditions is evaluated. A parameter for calculating error images for metabolite ratios is proposed and an effective way to display error images is shown. The results suggest that the average CRBs are strongly correlated with the standard deviations and hence that CRB values reflect the relative uncertainty of the calculated concentrations. The error information can be integrated directly into a metabolite image by displaying only those areas of the metabolite image with corresponding CRBs below a selected threshold or by mapping CRBs as a transparency of the metabolite image. The concept of error images avoids extensive examination of each SI spectrum and helps to reject low quality spectra.