Simulation of MR angiography imaging for validation of cerebral arteries segmentation algorithms
Simulation of MR angiography imaging for validation of cerebral arteries segmentation algorithms
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DOI：
10.1016/j.cmpb.2016.09.020
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发表时间：
2016-12-01
影响因子：
6.1
通讯作者：
Materka, Andrzej
中科院分区：
文献类型：
--
作者：
Klepaczko, Artur;Szczypinski, Piotr;Materka, Andrzej
背景和目的：磁共振血管成像(MRA)图像的准确血管分割对于计算机辅助诊断脑血管疾病(如狭窄或动脉瘤)至关重要。分割算法正确再现动脉系统几何形状的能力应该定量地表达出来，并且独立于观察者，以确保评估的客观性。方法：本文介绍了一种使用定制的MRA仿真框架来验证血管分割算法的方法。为此，基于实时飞行时间(TOF)MRA数据集，开发了一个逼真的颅内动脉树参考模型。在此基础上，利用不同的采集协议参数和信噪比，对血流进行了模拟，并合成了一系列TOF图像。然后使用血管建模工具包(VMTK)中提供的水平集分割算法重建合成的动脉树。此外，为了展示提出的方法的广泛应用，还对两种替代技术进行了验证：多尺度血管增强过滤器和基于水平集的方法的Chan-Vese变体，如在Insight分割和配准工具包(ITK)中实现的。结果：每种分割算法对确定血管中心线路径的准确率都很高(如果使用VMTK，平均错误率为5.6%)。然而，根据血管大小、图像采集和分割方法的不同，估计的半径与地面真实值存在偏差，平均误差率在7%到79%之间。结论：所设计的MRA模拟器是定量验证MRA图像处理算法的可靠工具，提供了客观、可重复性的结果，并且与观察者无关。(C)2016爱思唯尔爱尔兰有限公司。保留所有权利。
Background and objective: Accurate vessel segmentation of magnetic resonance angiography (MRA) images is essential for computer-aided diagnosis of cerebrovascular diseases such as stenosis or aneurysm. The ability of a segmentation algorithm to correctly reproduce the geometry of the arterial system should be expressed quantitatively and observer-independently to ensure objectivism of the evaluation.Methods: This paper introduces a methodology for validating vessel segmentation algorithms using a custom-designed MRA simulation framework. For this purpose, a realistic reference model of an intracranial arterial tree was developed based on a real Time-of-Flight (TOF) MRA data set. With this specific geometry blood flow was simulated and a series of TOF images was synthesized using various acquisition protocol parameters and signal-to-noise ratios. The synthesized arterial tree was then reconstructed using a level-set segmentation algorithm available in the Vascular Modeling Toolkit (VMTK). Moreover, to present versatile application of the proposed methodology, validation was also performed for two alternative techniques: a multi-scale vessel enhancement filter and the Chan-Vese variant of the level-set-based approach, as implemented in the Insight Segmentation and Registration Toolkit (ITK). The segmentation results were compared against the reference model.Results: The accuracy in determining the vessels centerline courses was very high for each tested segmentation algorithm (mean error rate = 5.6% if using VMTK). However, the estimated radii exhibited deviations from ground truth values with mean error rates ranging from 7% up to 79%, depending on the vessel size, image acquisition and segmentation method.Conclusions: We demonstrated the practical application of the designed MRA simulator as a reliable tool for quantitative validation of MRA image processing algorithms that provides objective, reproducible results and is observer independent. (C) 2016 Elsevier Ireland Ltd. All rights reserved.