基于表面轮廓和集合支持向量机的颞上沟褶皱通道自动检测

Tianqi Song, C. Bodin, O. Coulon
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引用次数: 0

摘要

皮层折叠是大脑皮层的一个基本特征,在个体之间表现出差异。Plis de passages (PPs),即埋在褶皱内部的邻近脑回,可以部分解释这种变异性。然而,一种系统的自动检测所有PPs的方法仍然不可用。本文提出了一种自动检测脑皮层PPs的方法。我们首先通过表面轮廓提取皮层局部区域的几何信息。然后,提出了一种集成支持向量机(SVM)来识别pp。实验结果表明了该方法的有效性和鲁棒性。
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Automatic Detection of Plis De Passage in the Superior Temporal Sulcus using Surface Profiling and Ensemble SVM
Cortical folding, an essential characteristic of the brain cortex, shows variability across individuals. Plis de passages (PPs), namely annectant gyri buried inside the fold, can explain part of the variability. However, a systematic method of automatically detecting all PPs is still not available. In this paper, we present a method to detect the PPs on the cortex automatically. We first extract the geometry information of the localized areas on the cortex via surface profiling. Then, an ensemble support vector machine (SVM) is developed to identify the PPs. Experimental results show the effectiveness and robustness of our method.
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