Segmentation of high angular resolution diffusion MRI modeled as a field of von Mises-Fisher mixtures
Segmentation of high angular resolution diffusion MRI modeled as a field of von Mises-Fisher mixtures
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DOI：
10.1007/11744078_36
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发表时间：
2006-01-01
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影响因子：
--
通讯作者：
Mareci, Thomas
中科院分区：
文献类型：
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作者：
McGraw, Tim;Vemuri, Baba;Mareci, Thomas
高角分辨率扩散成像（HARDI）允许在可能的位移方向的球体上计算水分子位移概率。这种概率通常被称为取向分布函数（ODF）。在本文中，我们提出了一种新的模型，即扩散ODF，冯Mises-Fisher（vMF）分布的混合物。我们的模型是紧凑的，因为它需要很少的变量来模拟复杂的ODF几何形状，特别是在存在异质性神经纤维取向。我们还提出了一个黎曼几何框架计算内在的距离，在封闭的形式，并执行插值的vMF混合物所代表的ODF之间。作为一个例子，我们应用内隐马尔可夫测度字段分割方案的内在距离。我们目前的结果，这种分割的HARDI图像的大鼠脊髓-这表明不同的区域内的白色和灰质。应该注意的是，这种灰色和白色物质的精细分割水平不能从对比MRI扫描或扩散张量MRI扫描中获得。我们通过将其应用于已知地面真实情况的合成数据集来验证分割算法。
High angular resolution diffusion imaging (HARDI) permits the computation of water molecule displacement probabilities over a sphere of possible displacement directions. This probability is often referred to as the orientation distribution function (ODF). In this paper we present a novel model for the diffusion ODF namely, a mixture of von Mises-Fisher (vMF) distributions. Our model is compact in that it requires very few variables to model complicated ODF geometries which occur specifically in the presence of heterogeneous nerve fiber orientation. We also present a Riemannian geometric framework for computing intrinsic distances, in closed-form, and performing interpolation between ODFs represented by vMF mixtures. As an example, we apply the intrinsic distance within a hidden Markov measure field segmentation scheme. We present results of this segmentation for HARDI images of rat spinal cords - which show distinct regions within both the white and gray matter. It should be noted that such a fine level of parcellation of the gray and white matter cannot be obtained either from contrast MRI scans or Diffusion Tensor MRI scans. We validate the segmentation algorithm by applying it to synthetic data sets where the ground truth is known.