偏差-方差权衡分析使用统一的CR界为SPECT系统

M. Usman, A. Hero, J. Fessler, W. Rogers
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引用次数: 6

摘要

作者量化的基本偏差-方差权衡的图像重建问题在放射药物断层扫描使用Cramer-Rao (CR)界分析。图像重建问题往往是有偏的,不能使用估计器均方误差性能的经典或无偏CR界。作者使用了最近发展的“一致”CR界,它适用于偏差梯度满足用户指定长度约束的有偏估计量。作者用几个不同的例子演示了在一个简单的SPECT系统中使用“均匀”CR界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bias-variance tradeoffs analysis using uniform CR bound for a SPECT system
The authors quantify fundamental bias-variance tradeoffs for the image reconstruction problem in radio-pharmaceutical tomography using Cramer-Rao (CR) bound analysis. The image reconstruction problem is very often biased and the classical or the unbiased CR bound on the mean square error performance of the estimator can not be used. The authors use a recently developed "uniform" CR bound which applies to biased estimators whose bias gradient satisfies a user specified length constraint. The authors demonstrate the use of the "uniform" CR bound for a simple SPECT system using several different examples.<>
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