AUTOMATED ANATOMICAL LABELING OF THE CEREBRAL ARTERIES USING BELIEF PROPAGATION.

AUTOMATED ANATOMICAL LABELING OF THE CEREBRAL ARTERIES USING BELIEF PROPAGATION.
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使用信仰传播对脑动脉进行自动解剖标记。

DOI:
10.1117/12.2006460
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发表时间:
2013-03-13
期刊:
Proceedings of SPIE--the International Society for Optical Engineering
影响因子:
--
通讯作者:
Prince JL
Prince JL
中科院分区:
其他
文献类型:
--
作者:
Bilgel M;Roy S;Carass A;Nyquist PA;Prince JL

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脑血管的标记对于表征解剖变异、量化与特定血管相关的脑形态以及血管特性和异常的受试者之间的比较是很重要的。我们提出了一种基于贝叶斯网络表示的血管树的统计推理方法来自动标记大脑动脉的前部。我们的方法将使用血管中心线特征训练的随机森林分类器获得的概率与结合大脑动脉网络连接概率的置信度传播方法相结合。我们在30个受试者上使用留一法验证来评估我们的方法,结果表明它达到了92%以上的平均正确的血管标记率。
Labeling of cerebral vasculature is important for characterization of anatomical variation, quantification of brain morphology with respect to specific vessels, and inter-subject comparisons of vessel properties and abnormalities. We propose an automated method to label the anterior portion of cerebral arteries using a statistical inference method on the Bayesian network representation of the vessel tree. Our approach combines the likelihoods obtained from a random forest classifier trained using vessel centerline features with a belief propagation method integrating the connection probabilities of the cerebral artery network. We evaluate our method on 30 subjects using a leave-one-out validation, and show that it achieves an average correct vessel labeling rate of over 92%.
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