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Morphometric analysis of white matter lesions in MR images: method and validation.磁共振图像中脑白质病变的形态计量分析:方法与验证。
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The imaging appearance of Creutzfeldt-Jakob disease caused by the E200K mutation.由E200K突变引起的克雅氏病的影像学表现。
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Human cerebral cortex: a system for the integration of volume- and surface-based representations.人类大脑皮层:一个用于整合基于体积和表面表征的系统。
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Age and gender effects on human brain anatomy: a voxel-based morphometric study in healthy elderly.年龄和性别对人类脑解剖结构的影响:一项针对健康老年人的基于体素的形态计量学研究。
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Unified segmentation.统一分割
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Reproducibility and accuracy of quantitative magnetic resonance imaging techniques of whole-brain atrophy measurement in multiple sclerosis.多发性硬化症全脑萎缩测量的定量磁共振成像技术的可重复性和准确性
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Sequence-independent segmentation of magnetic resonance images.磁共振图像的序列无关分割
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使用SPM5和SIENAX对脑部分割进行交叉验证。

Cross-validation of brain segmentation by SPM5 and SIENAX.

作者信息

Lee Hedok, Prohovnik Isak

机构信息

Department of Psychiatry, Mount Sinai School of Medicine, New York, NY, USA.

出版信息

Psychiatry Res. 2008 Nov 30;164(2):172-7. doi: 10.1016/j.pscychresns.2007.12.008. Epub 2008 Oct 18.

DOI:10.1016/j.pscychresns.2007.12.008
PMID:18930381
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2778005/
Abstract

Volumes of cerebral grey (GM) or white matter (WM) are often used as clinical observations or statistical covariates. Several automated segmentation tools can be used for this purpose, but they have not been validated against each other. We used the most common ones, SPM5 and SIENAX 2.4, to derive volumes of grey and white matter in 56 healthy subjects (mean age 49+/-13, range 22-80) and compared the two methods. Both methods yielded significant correlations with age in the expected directions, and estimates of parenchymal volumes were highly correlated. However, without use of prior probability maps, or priors, in SIENAX, GM was significantly underestimated in comparison to SPM (0.52+/-.06 vs 0.66+/-.07 L) and WM was significantly overestimated (0.48+/-.07 vs 0.46+/-.07 L). This error was associated with misclassification of GM as cerebrospinal fluid, especially in deep grey matter. Invoking prior probabilities in SIENAX resulted in excellent agreement with SPM: GM and WM volumes were found to be 0.64+/-0.07 L and 0.47+/-0.07 L, respectively. We conclude that SIENAX requires priors for accurate volumetric estimates, and then provides close agreement with SPM5.

摘要

脑灰质(GM)或白质(WM)的体积常被用作临床观察指标或统计协变量。有几种自动分割工具可用于此目的,但它们之间尚未相互验证。我们使用了最常用的两种工具SPM5和SIENAX 2.4,来得出56名健康受试者(平均年龄49±13岁,范围22 - 80岁)的灰质和白质体积,并比较这两种方法。两种方法在预期方向上均与年龄有显著相关性,实质体积的估计值高度相关。然而,在SIENAX中,若不使用先验概率图或先验信息,与SPM相比,GM被显著低估(0.52±0.06 L对0.66±0.07 L),而WM被显著高估(0.48±0.07 L对0.46±0.07 L)。这种误差与GM被误分类为脑脊液有关,尤其是在深部灰质中。在SIENAX中引入先验概率后,与SPM达成了极佳的一致性:GM和WM体积分别为0.64±0.07 L和0.47±0.07 L。我们得出结论,SIENAX需要先验信息以进行准确的体积估计,然后才能与SPM5达成紧密一致。