A system to detect cerebral aneurysms in multimodality angiographic data sets
A system to detect cerebral aneurysms in multimodality angiographic data sets
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DOI：
10.1118/1.4890775
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发表时间：
2014-09-01
期刊：
影响因子：
3.8
通讯作者：
Toennies, Klaus D.
中科院分区：
文献类型：
--
作者：
Hentschke, Clemens M.;Beuing, Oliver;Toennies, Klaus D.
目的：早期发现脑动脉瘤在预防蛛网膜下腔出血中起着重要作用。作者提出了一种在多模态3D血管造影数据集中自动检测脑动脉瘤的系统。作者的系统是参数化的对比增强磁共振血管造影术（CE-MRA），飞行时间磁共振血管造影术（TOF-MRA），和计算机断层扫描血管造影术（CTA）。在线性判别函数（LDF）中组合了几个特征，以区分真正的动脉瘤和假阳性。这些特征包括形状信息、空间信息和概率信息。LDF可以由领域专家参数化，也可以通过训练自动参数化。血管分割是避免，因为它可能会严重影响检测algorithm.Results：作者测试了他们的方法与151临床血管造影数据集，其中包含112个动脉瘤。作者使用CE-MRA数据集达到了95%的灵敏度，每个数据集的平均假阳性率（FPDS）为8.2。对于TOF-MRA，我们在11.3 FPDS时达到95%的灵敏度。对于CTA，我们在22.8 FPDS时达到95%的灵敏度。对于所有模式，专家参数化导致类似或更好的结果比训练有素的参数化，消除了培训的需要。93%的动脉瘤小于5 mm的发现。作者还表明，他们的算法是能够检测动脉瘤，以前被忽视的放射科医生。结论：作者提出了一个自动系统来检测脑动脉瘤的多模式血管造影数据集。该系统被证明是一个合适的计算机辅助检测工具，以帮助放射科医生发现脑动脉瘤。(C)2014年美国医学物理学家协会。
Purpose: The early detection of cerebral aneurysms plays a major role in preventing subarachnoid hemorrhage. The authors present a system to automatically detect cerebral aneurysms in multimodal 3D angiographic data sets. The authors' system is parametrizable for contrast-enhanced magnetic resonance angiography (CE-MRA), time-of-flight magnetic resonance angiography (TOF-MRA), and computed tomography angiography (CTA).Methods: Initial volumes of interest are found by applying a multiscale sphere-enhancing filter. Several features are combined in a linear discriminant function (LDF) to distinguish between true aneurysms and false positives. The features include shape information, spatial information, and probability information. The LDF can either be parametrized by domain experts or automatically by training. Vessel segmentation is avoided as it could heavily influence the detection algorithm.Results: The authors tested their method with 151 clinical angiographic data sets containing 112 aneurysms. The authors reach a sensitivity of 95% with CE-MRA data sets at an average false positive rate per data set (FPDS) of 8.2. For TOF-MRA, we achieve 95% sensitivity at 11.3 FPDS. For CTA, we reach a sensitivity of 95% at 22.8 FPDS. For all modalities, the expert parametrization led to similar or better results than the trained parametrization eliminating the need for training. 93% of aneurysms that were smaller than 5 mm were found. The authors also showed that their algorithm is capable of detecting aneurysms that were previously overlooked by radiologists.Conclusions: The authors present an automatic system to detect cerebral aneurysms in multimodal angiographic data sets. The system proved as a suitable computer-aided detection tool to help radiologists find cerebral aneurysms. (C) 2014 American Association of Physicists in Medicine.