AN IMPROVED UNBIASED METHOD FOR DIFFSPECT QUANTIFICATION IN EPILEPSY.
AN IMPROVED UNBIASED METHOD FOR DIFFSPECT QUANTIFICATION IN EPILEPSY.
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一种改进的癫痫离散量化无偏方法。
DOI：
10.1109/isbi.2009.5193205
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Papademetris,Xenophon
中科院分区：
文献类型：
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作者：
Scheinost,Dustin;Blumenfeld,Hal;Papademetris,Xenophon
确定癫痫发作的区域对治疗医学上难治性癫痫至关重要。发作期和间歇期单光子发射计算机断层扫描（SPECT）图像的比较已被证明在局灶性癫痫的定位上是成功的。统计参数映射（ISAS）算法是比较这些图像比较成功的算法之一。然而，ISAS受到其统计设计的限制。该设计在序列SPECT图像的正态方差估计中引入了扫描顺序偏差。我们通过估计半正态分布的正态方差来纠正这种偏差。在本文中，我们提出了一种基于原始ISAS算法的更新算法（ISAS HN），该算法具有更正的正态方差估计和ISAS HN的开源实用程序。
Determining the region of seizure onset is of critical importance for treating medically intractable epilepsy. Comparisons between an ictal and interictal Single Photon Emission Computed Tomography (SPECT) images have been shown to be successful in localizing focal epilepsy. The Ictal-Interictal Subtraction Analysis by Statistical Parametric Mapping (ISAS) algorithm remains one the more successful algorithms for comparing these images. However ISAS is limited by its statistical design. This design introduces a scan order bias in the estimation of the normal variance of sequential SPECT images. We have corrected this bias by estimating the normal variance with a half-normal distribution. In this paper we present an updated algorithm (ISAS HN) based on the original ISAS algorithm with a corrected estimate of the normal variance and an open-source utility for ISAS HN.