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Multi-shelled q -ball Imaging: Moment-based Orientation Distribution Function

机译:多壳q球成像:基于矩的方向分布函数

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Purpose: q -ball imaging (QBI) reconstructs the orientation distribution function (ODF) that describes the probability for a spin to diffuse in a given direction, and it is capable of identifying intravoxel multiple fiber orientations. The local maxima of ODF are assumed to indicate fiber orientations, but there is a mismatch between the orientation of a fiber crossing and the local maxima. We propose a novel method, multi-shelled QBI (MS-QBI), that gives a new ODF based on the moment of the probability density function of diffusion displacement. We test the accuracy of the fiber orientation indicated by the new ODF and test fiber tracking using the new ODF. Methods: We performed tests using numerical simulation. To test the accuracy of fiber orientation, we assumed that 2 fibers cross and evaluated the deviation of the measured crossing angle from the actual angle. To test the fiber tracking, we used a numerical phantom of the cerebral hemisphere containing the corpus callosum, projection fibers, and superior longitudinal fasciculus. In the tests, we compared the results between MS-QBI and conventional QBI under the condition of approximately equal total numbers of diffusion signal samplings between the 2 methods and chose the interpolation parameter such that the stabilities of the results of the angular deviation for the 2 methods were the same. Results: The absolute value of the mean angular deviation was smaller in MS-QBI than in conventional QBI. Using the moment-based ODF improved the accuracy of fiber pathways in fiber tracking but maintained the stability of the results. Conclusion: MS-QBI can more accurately identify intravoxel multiple fiber orientations than can QBI, without increasing sampling number. The high accuracy of MS-QBI will contribute to the improved tractography.
机译:目的:q球成像(QBI)重建了方向分布函数(ODF),该函数描述了旋转在给定方向上扩散的可能性,并且能够识别体素内多个纤维的方向。假定ODF的局部最大值指示纤维方向,但是纤维交叉的方向和局部最大值之间不匹配。我们提出了一种新颖的方法,多壳QBI(MS-QBI),它基于扩散位移的概率密度函数的矩给出了一个新的ODF。我们测试了新ODF指示的光纤定向的准确性,并使用新ODF测试了光纤跟踪。方法:我们使用数值模拟进行了测试。为了测试纤维定向的准确性,我们假设2根纤维交叉,并评估了所测交叉角与实际角度的偏差。为了测试纤维追踪,我们使用了大脑半球的数字体模,其中包含call体,投射纤维和上纵束。在测试中,我们比较了两种方法之间在扩散信号采样总数大致相等的情况下MS-QBI与常规QBI的结果,并选择了插值参数,以使两种方法的角度偏差结果具有稳定性方法是相同的。结果:MS-QBI中平均角度偏差的绝对值小于常规QBI。使用基于矩的ODF可以提高光纤跟踪中光纤路径的准确性,但可以保持结果的稳定性。结论:与QBI相比,MS-QBI可以更准确地识别体素内多个纤维方向,而无需增加采样数。 MS-QBI的高准确度将有助于改善超声检查。

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