Tract orientation mapping for bundle-specific tractography
Tract orientation mapping for bundle-specific tractography
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DOI：
10.1007/978-3-030-00931-1_5
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发表时间：
2018-06
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通讯作者：
J. Wasserthal;P. Neher;Klaus Maier-Hein
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作者：
J. Wasserthal;P. Neher;Klaus Maier-Hein
虽然主要的白色物质束在神经科学和医学的许多研究中具有极大的兴趣，但是从弥散MRI纤维束图中在较大的队列中对其进行手动解剖是耗时的，需要专业知识并且难以再现。束定向映射（TOM）是一种新颖的概念，其基于从原始纤维定向分布函数（fODF）峰值到束定向图（也缩写为fODF）列表的学习映射来促进纤维束特异性纤维束成像。TOM）。每个TOM表示一个已知的束，每个体素包含不超过一个方向矢量。TOM可以作为纤维束成像的先验信息甚至直接输入。我们使用编码器-解码器全卷积神经网络架构来学习所需的映射。与以前的概念相比，特定束的重建，所提出的一个避免了各种繁琐的处理步骤，如全脑纤维束成像，图谱配准或聚类。我们将其与来自人类连接组项目的105名受试者中的20种不同束的四种最先进束识别方法进行比较。即使对于困难的管道，结果也具有解剖学上的说服力，同时达到低角度误差，前所未有的运行时间和最高精度值（Dice）。我们的代码和数据是公开的。
While the major white matter tracts are of great interest to numerous studies in neuroscience and medicine, their manual dissection in larger cohorts from diffusion MRI tractograms is time-consuming, requires expert knowledge and is hard to reproduce. Tract orientation mapping (TOM) is a novel concept that facilitates bundle-specific tractography based on a learned mapping from the original fiber orientation distribution function (fODF) peaks to a list of tract orientation maps (also abbr. TOM). Each TOM represents one of the known tracts with each voxel containing no more than one orientation vector. TOMs can act as a prior or even as direct input for tractography. We use an encoder-decoder fully-convolutional neural network architecture to learn the required mapping. In comparison to previous concepts for the reconstruction of specific bundles, the presented one avoids various cumbersome processing steps like whole brain tractography, atlas registration or clustering. We compare it to four state of the art bundle recognition methods on 20 different bundles in a total of 105 subjects from the Human Connectome Project. Results are anatomically convincing even for difficult tracts, while reaching low angular errors, unprecedented runtimes and top accuracy values (Dice). Our code and our data are openly available.