Automated detection of intracranial aneurysms based on parent vessel 3D analysis
Automated detection of intracranial aneurysms based on parent vessel 3D analysis
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DOI：
10.1016/j.media.2009.10.005
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发表时间：
2010-04-01
影响因子：
10.9
通讯作者：
Malek, Adel M.
中科院分区：
文献类型：
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作者：
Lauric, Alexandra;Miller, Eric;Malek, Adel M.
脑动脉瘤的检测在降低颅内蛛网膜下腔出血（SAH）的发生率方面发挥着关键作用，SAH的发病率和死亡率很高。大多数非创伤性SAH病例是由颅内动脉瘤破裂引起的，准确的检测可以显著降低误诊病例的比例。本研究提出一个自动侦测颅内动脉瘤的方案。应用于分割的脑血管系统，该方法检测动脉瘤作为血管树上的可疑区域，并且被设计为辅助诊断医生进行解释，从而减少漏诊。在当前的方法中，血管被分割并且其中轴被计算。沿着血管的小区域沿着被检查，并且扭曲数被引入作为新的表面描述符，以量化任何给定区域接近管状结构的程度。动脉瘤被检测为血管树的非管状区域。分析和实验验证的几何假设的方法进行了研究。该方法在3D旋转血管造影（3D-RA）和计算机断层扫描血管造影（CTA）上进行了测试。在我们的实验中，实现了100%的灵敏度，3D-RA数据的平均假阳性率为0.66，CTA数据的平均假阳性率为5.36。(C)2009爱思唯尔有限公司版权所有。
The detection of brain aneurysms plays a key role in reducing the incidence of intracranial subarachnoid hemorrhage (SAH) which carries a high rate of morbidity and mortality. The majority of non-traumatic SAH cases is caused by ruptured intracranial aneurysms and accurate detection can decrease a significant proportion of misdiagnosed cases. A scheme for automated detection of intracranial aneurysms is proposed in this study. Applied to the segmented cerebral vasculature, the method detects aneurysms as suspect regions on the vascular tree, and is designed to assist diagnosticians with their interpretations and thus reduce missed detections. In the current approach, the vessels are segmented and their medial axis is computed. Small regions along the vessels are inspected and the writhe number is introduced as a new Surface descriptor to quantify how closely any given region approximates a tubular structure. Aneurysms are detected as non-tubular regions of the vascular tree. The geometric assumptions underlying the approach are investigated analytically and validated experimentally. The method is tested on 3D-rotational angiography (3D-RA) and computed tomography angiography (CTA). In our experiments, 100% sensitivity was achieved with average false positives rates of 0.66 per study on 3D-RA data and 5.36 false positive rates per Study on CTA data. (C) 2009 Elsevier B.V. All rights reserved.