A comprehensive testing protocol for MRI neuroanatomical segmentation techniques: Evaluation of a novel lateral ventricle segmentation method.
A comprehensive testing protocol for MRI neuroanatomical segmentation techniques: Evaluation of a novel lateral ventricle segmentation method.
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DOI：
10.1016/j.neuroimage.2011.06.080
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发表时间：
2011-10-15
期刊：
影响因子：
5.7
通讯作者：
Simmons, Andrew
中科院分区：
文献类型：
--
作者：
Kempton, Matthew J.;Underwood, Tracy S. A.;Brunton, Simon;Stylios, Floris;Schmechtig, Anne;Ettinger, Ulrich;Smith, Marcus S.;Lovestone, Simon;Crum, William R.;Frangou, Sophia;Williams, Steven C. R.;Simmons, Andrew
虽然已经开发了各种各样的方法来自动评估MRI的脑区域体积，但这些算法在不同扫描仪和脉冲序列上的可重复性，它们在不同临床人群中的准确性以及对脑体积实际变化的敏感性并不总是得到全面的检验。首先，我们提出了一个全面的测试方案，其中包括312张免费提供的MR图像，以评估自动脑分割技术的准确性，再现性和灵敏度。对婴儿、年轻人和阿尔茨海默病患者的准确性进行了评估，并与基于卡瓦列里原理的专家观察者使用手工技术进行的金标准测量进行了比较。该方案确定了扫描会话、不同MRI脉冲序列以及1.5T和3T场强之间分割的可靠性，并使用大型纵向数据集检验了它们对体积微小变化的敏感性。其次，我们将该测试协议应用于一种新的侧脑室分割算法，并将其性能与广泛使用的FSL FIRST和FreeSurfer方法进行比较。测试方案产生的准确性，可靠性和灵敏度的定量措施侧脑室容量估计为每个分割方法。该算法在所有种群中具有较高的准确性（类内相关系数，ICC>0.95）， MRI脉冲序列之间具有良好的再现性（ICC>0.99），并且对纵向数据的年龄相关变化敏感。FreeSurfer具有较高的准确度（ICC>0.95）、良好的再现性（ICC>0.99）和灵敏度，而FSL FIRST在年轻成人和婴儿中具有良好的准确性（ICC>0.90）和良好的再现性（ICC=0.98），但在阿尔茨海默病患者或具有大脑室的健康受试者中无法分割心室容量。使用相同的计算机系统，新算法和FSL FIRST在不到10分钟内处理了一张MRI图像，而FreeSurfer则需要大约7个小时。所提出的测试方案可以比较不同算法的准确性、再现性和灵敏度。我们还证明了新的分割算法和FreeSurfer在确定侧室容积方面都是有效的，并且非常适合于多中心和纵向MRI研究。
Although a wide range of approaches have been developed to automatically assess the volume of brain regions from MRI, the reproducibility of these algorithms across different scanners and pulse sequences, their accuracy in different clinical populations and sensitivity to real changes in brain volume has not always been comprehensively examined. Firstly we present a comprehensive testing protocol which comprises 312 freely available MR images to assess the accuracy, reproducibility and sensitivity of automated brain segmentation techniques. Accuracy is assessed in infants, young adults and patients with Alzheimer’s disease in comparison to gold standard measures by expert observers using a manual technique based on Cavalieri’s principle. The protocol determines the reliability of segmentation between scanning sessions, different MRI pulse sequences and 1.5T and 3T field strengths and examines their sensitivity to small changes in volume using a large longitudinal dataset. Secondly we apply this testing protocol to a novel algorithm for segmenting the lateral ventricles and compare its performance to the widely used FSL FIRST and FreeSurfer methods. The testing protocol produced quantitative measures of accuracy, reliability and sensitivity of lateral ventricle volume estimates for each segmentation method. The novel algorithm showed high accuracy in all populations (intraclass correlation coefficient, ICC>0.95), good reproducibility between MRI pulse sequences (ICC>0.99) and was sensitive to age related changes in longitudinal data. FreeSurfer demonstrated high accuracy (ICC>0.95), good reproducibility (ICC>0.99) and sensitivity whilst FSL FIRST showed good accuracy in young adults and infants (ICC>0.90) and good reproducibility (ICC=0.98), but was unable to segment ventricular volume in patients with Alzheimer’s disease or healthy subjects with large ventricles. Using the same computer system, the novel algorithm and FSL FIRST processed a single MRI image in less than 10 minutes while FreeSurfer took approximately 7 hours. The testing protocol presented enables the accuracy, reproducibility and sensitivity of different algorithms to be compared. We also demonstrate that the novel segmentation algorithm and FreeSurfer are both effective in determining lateral ventricular volume and are well suited for multicentre and longitudinal MRI studies.
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影响因子：
5.7
作者：
Jovicich J;Czanner S;Han X;Salat D;van der Kouwe A;Quinn B;Pacheco J;Albert M;Killiany R;Blacker D;Maguire P;Rosas D;Makris N;Gollub R;Dale A;Dickerson BC;Fischl B
通讯作者：
Fischl B
影响因子：
5.7
作者：
Babalola, Kolawole Oluwole;Patenaude, Brian;Rueckert, Daniel
通讯作者：
Rueckert, Daniel
DOI：
10.1016/j.compmedimag.2008.10.008
发表时间：
2009-03-01
影响因子：
5.7
作者：
Chao, Wen-Hung;Chen, You-Yin;Tsang, Siny
通讯作者：
Tsang, Siny
影响因子：
--
作者：
Ettinger, Ulrich;Picchioni, Marco;Murray, Robin M.
通讯作者：
Murray, Robin M.
影响因子：
5.7
作者：
Gousias, Ioannis S.;Rueckert, Daniel;Hammers, Alexander
通讯作者：
Hammers, Alexander