基于主题间连接的一致分割验证

S. Lefranc, P. Roca, M. Perrot, C. Poupon, O. Coulon, D. Bihan, L. Hertz-Pannier, J. F. Mangin, D. Rivière
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引用次数: 1

摘要

将皮质表面划分为具有均匀的基于dmri的连接概况的区域是一个有希望但具有挑战性的主题。本文扩展了Roca[1]提出的基于主体间连通性的皮层分割框架。首先,我们通过调优参数实现了最先进的算法,然后在大型高质量ARCHI数据库上提出了一种经过验证的改进算法。该算法包括在合理的时间内对每个回进行聚类和细分。交叉验证表明结果模式在不同组之间是可重复的。稳定性说明了三组不同的受试者的后中枢回。最后,该方法对跟踪类型、皮质网格特征和脑回边界等初始条件具有鲁棒性。
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Validation of consistent inter-subject connectivity-based parcellation
Splitting the cortical surface into regions with homogeneous dMRI-based connectivity profiles is a promising but challenging topic. This paper extends the inter-subject connectivity-based cortex parcellation framework proposed by Roca [1]. In a first step, we implement the state-of-the-art algorithm with tuned parameters and, then propose a refined algorithm validated on the large high quality ARCHI database. This algorithm consists in clustering and subdividing each gyrus, in a reasonable time. Cross-validation shows that the resulting patterns are reproducible across groups. The stability is illustrated for the post-central gyrus of three different groups of subjects. Finally, the method has successfully been made robust to initial conditions: tracking type, cortical mesh characteristics and boundaries of gyri.
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