结构张量分析用于脑组织显微定向估计的验证。

IF 2.3 4区 医学 Q2 BIOCHEMICAL RESEARCH METHODS
Journal of Neuroscience Methods Pub Date : 2025-11-01 Epub Date: 2025-07-28 DOI:10.1016/j.jneumeth.2025.110539
Bryson Gray, Andrew W Smith, Allan MacKenzie-Graham, David W Shattuck, Daniel J Tward
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引用次数: 0

摘要

背景:利用弥散性MRI准确定位白质通路对于研究大脑连通性至关重要,但目前方法的准确性尚不完全清楚。验证准确性的有效方法是考虑与尸检样本的MRI共同注册的显微镜数据。在这种情况下,结构张量分析是计算局部方向的标准方法。然而,结构张量分析本身还没有得到很好的验证,并且在角度分辨率和特定空间尺度的选择性方面存在不确定性。新方法:在这里,我们进行了一项模拟研究,以研究使用结构张量来估计纤维排列在有和没有交叉的配置中的方向的准确性。结果:我们研究了一系列模拟条件,重点研究了该方法在具有各向异性分辨率的图像上的行为,这在显微镜数据采集中特别常见。我们还分析了二维和三维光学显微镜数据。结果表明,结构张量分析中参数的选择对单方向估计精度的影响较小,但精度会随着分辨率各向异性的增加而降低。另一方面,当估计交叉纤维的方向时,参数的选择变得至关重要,而糟糕的选择导致方向估计基本上是随机的。结论:本研究为研究人员在脑成像数据轴突方向研究中有效应用结构张量分析提供了一套建议,并量化了该方法的局限性,特别是在各向异性数据的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Validation of structure tensor analysis for orientation estimation in brain tissue microscopy.

Background: Accurate localization of white matter pathways using diffusion MRI is critical to investigating brain connectivity, but the accuracy of current methods is not thoroughly understood. A fruitful approach to validating accuracy is to consider microscopy data that have been co-registered with MRI of post mortem samples. In this setting, structure tensor analysis is a standard approach to computing local orientations. However, structure tensor analysis itself has not been well-validated and is subject to uncertainty in its angular resolution, and selectivity to specific spatial scales.

New method: Here, we conducted a simulation study to investigate the accuracy of using structure tensors to estimate the orientations of fibers arranged in configurations with and without crossings.

Results: We examined a range of simulated conditions, with a focus on investigating the method's behavior on images with anisotropic resolution, which is particularly common in microscopy data acquisition. We also analyzed 2D and 3D optical microscopy data.

Comparison with existing methods: Our results show that parameter choice in structure tensor analysis has relatively little effect on accuracy for estimating single orientations, although accuracy decreases with increasing resolution anisotropy. On the other hand, when estimating the orientations of crossing fibers, the choice of parameters becomes critical, and poor choices result in orientation estimates that are essentially random.

Conclusions: This work provides a set of recommendations for researchers seeking to apply structure tensor analysis effectively in the study of axonal orientations in brain imaging data and quantifies the method's limitations, particularly in the case of anisotropic data.

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来源期刊
Journal of Neuroscience Methods
Journal of Neuroscience Methods 医学-神经科学
CiteScore
7.10
自引率
3.30%
发文量
226
审稿时长
52 days
期刊介绍: The Journal of Neuroscience Methods publishes papers that describe new methods that are specifically for neuroscience research conducted in invertebrates, vertebrates or in man. Major methodological improvements or important refinements of established neuroscience methods are also considered for publication. The Journal''s Scope includes all aspects of contemporary neuroscience research, including anatomical, behavioural, biochemical, cellular, computational, molecular, invasive and non-invasive imaging, optogenetic, and physiological research investigations.
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