Beyond crossing fibers: bootstrap probabilistic tractography using complex subvoxel fiber geometries.
Beyond crossing fibers: bootstrap probabilistic tractography using complex subvoxel fiber geometries.
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DOI：
10.3389/fneur.2014.00216
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发表时间：
2014
影响因子：
3.4
通讯作者：
Pike GB
中科院分区：
文献类型：
--
作者：
Campbell JS;MomayyezSiahkal P;Savadjiev P;Leppert IR;Siddiqi K;Pike GB
扩散磁共振成像纤维束成像是研究活体人类脑白质连通性的有力工具。然而，它容易出现假阳性和假阴性结果，使得对气管造影术结果的解释变得困难。最佳的纤维束成像必须从准确描述亚体素白质纤维的结构开始，包括量化所获得的纤维方向上的不确定性，并量化每个重建纤维束的置信度。本文提出了一种满足上述要求的新型、全面的纤维束成像管路。使用一种不仅允许直交叉纤维，而且允许弯曲和张开的纤维的技术，详细描述了亚体素纤维的几何形状。为了有效地量化所获得的子体素几何中的不确定性，在剩余自举统计过程中重复执行该技术。定义了一个稳健的连通性指数来量化重建连接的置信度。在人脑中演示了纤维束成像管道。
Diffusion magnetic resonance imaging fiber tractography is a powerful tool for investigating human white matter connectivity in vivo. However, it is prone to false positive and false negative results, making interpretation of the tractography result difficult. Optimal tractography must begin with an accurate description of the subvoxel white matter fiber structure, includes quantification of the uncertainty in the fiber directions obtained, and quantifies the confidence in each reconstructed fiber tract. This paper presents a novel and comprehensive pipeline for fiber tractography that meets the above requirements. The subvoxel fiber geometry is described in detail using a technique that allows not only for straight crossing fibers but for fibers that curve and splay. This technique is repeatedly performed within a residual bootstrap statistical process in order to efficiently quantify the uncertainty in the subvoxel geometries obtained. A robust connectivity index is defined to quantify the confidence in the reconstructed connections. The tractography pipeline is demonstrated in the human brain.
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