An automated registration algorithm for measuring MRI subcortical brain structures
An automated registration algorithm for measuring MRI subcortical brain structures
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DOI：
10.1006/nimg.1997.0274
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发表时间：
1997-07-01
期刊：
影响因子：
5.7
通讯作者：
McCarley, RW
中科院分区：
文献类型：
--
作者：
Iosifescu, DV;Shenton, ME;McCarley, RW
使用自动配准算法将解剖磁共振（MR）图谱弹性匹配到个体脑磁共振图像上。我们的目的是评估这种测量MRI脑结构体积的方法的准确性。我们对14名精神分裂症患者和14名正常对照者的一系列28张MR脑图像应用了两种连续的算法。首先，我们使用自动分割程序来区分白质、皮层和皮层下灰质和脑脊液。接下来，我们通过匹配白质和皮层下灰质表面，对图谱分割进行弹性变形，以适应受试者的大脑。为了评估这些测量的准确性，我们将所有28张图像中的11个大脑结构与MRI扫描中手动追踪的相同结构进行了比较。测量结果之间的相似性（手动和自动体积之间的相对差异）在整个白质中为97%，在整个灰质中为92%，在皮层下结构中平均为89%，在整个白质中，手动和自动体积之间的相对空间重叠度为97%，在整个灰质中为92%，在皮层下结构中平均为75%。对于用自动和手动方法绘制的所有对结构，Pearson相关性在r = 0.78和r = 0.98之间（P < 0.01,N = 28），除了苍白球，其中r = 0.55（左）和r = 0.44（右）（P < 0.01,N = 28）。在精神分裂症组中，与对照组相比，我们发现基底节区（即尾状核、壳核和苍白球）的MRI体积增加了16.7%，但总的灰质/白质体积或丘脑MR体积没有差异。这一发现再现了先前报道的结果，这些结果是在相同的患者群体中通过手动绘制结构获得的，并表明我们的自动注册算法比更多劳动密集型的手动跟踪更实用/有效。(C) 1997学术出版社。
An automated registration algorithm was used to elastically match an anatomical magnetic resonance (MR) atlas onto individual brain MR images. Our goal was to evaluate the accuracy of this procedure for measuring the volume of MRI brain structures. We applied two successive algorithms to a series of 28 MR brain images, from 14 schizophrenia patients and 14 normal controls. First, we used an automated segmentation program to differentiate between white matter, cortical and subcortical gray matter, and cerebrospinal fluid. Next, we elastically deformed the atlas segmentation to fit the subject's brain, by matching the white matter and subcortical gray matter surfaces, To assess the accuracy of these measurements, we compared, on all 28 images, 11 brain structures, measured with elastic matching, with the same structures traced manually on MRI scans. The similarity between the measurements (the relative difference between the manual and the automated volume) was 97% for whole white matter, 92% for whole gray matter, and on average 89% for subcortical structures, The relative spatial overlap between the manual and the automated volumes was 97% for whole white matter, 92% for whole gray matter, and on average 75% for subcortical structures. For all pairs of structures rendered with the automated and the manual method, Pearson correlations were between r = 0.78 and r = 0.98 (P < 0.01, N = 28), except for globus pallidus, where r = 0.55 (left) and r = 0.44 (right) (P < 0.01,N = 28). In the schizophrenia group, compared to the controls, we found a 16.7% increase in MRI volume for the basal ganglia (i.e., caudate nucleus, putamen, and globus pallidus), but no difference in total gray/white matter volume or in thalamic MR volume. This finding reproduces previously reported results, obtained in the same patient population with manually drawn structures, and suggests the utility/efficacy of our automated registration algorithm over more labor-intensive manual tracings. (C) 1997 Academic Press.