首页> 外文期刊>Journal of the Royal Society Interface >Automated segmentation of the lamina cribrosa using Frangi's filter: a novel approach for rapid identification of tissue volume fraction and beam orientation in a trabeculated structure in the eye
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Automated segmentation of the lamina cribrosa using Frangi's filter: a novel approach for rapid identification of tissue volume fraction and beam orientation in a trabeculated structure in the eye

机译:使用Frangi滤镜自动对筛板进行分割:一种新颖的方法,用于快速识别眼中小梁结构中的组织体积分数和束方向

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摘要

The lamina cribrosa (LC) is a tissue in the posterior eye with a complex trabecular microstructure. This tissue is of great research interest, as it is likely the initial site of retinal ganglion cell axonal damage in glaucoma. Unfortunately, the LCis difficult to access experimentally, and thus imaging techniques in tandem with image processing have emerged as powerful tools to study the microstructure and biomechanics of this tissue. Here, we present a staining approach to enhance the contrast of the microstructure in micro-computed tomography (micro-CT) imaging as well as a comparison between tissues imaged with micro-CT and second harmonic generation (SHG) microscopy. We then apply a modified version of Frangi's vesselness filter to automatically segment the connective tissue beams of the LC and determine the orientation of each beam. This approach successfully segmented the beams of a porcine optic nerve head from micro-CT in three dimensions and SHG microscopy in two dimensions. As an application of this filter, we present finite-element modelling of the posterior eye that suggests that connective tissue volume fraction is the major driving factor of LC biomechanics. We conclude that segmentation with Frangi's filter is a powerful tool for future image-driven studies of LC biomechanics.
机译:筛板(LC)是后眼组织,具有复杂的小梁微结构。该组织具有极大的研究兴趣,因为它可能是青光眼中视网膜神经节细胞轴突损伤的最初部位。不幸的是,LC很难通过实验获得,因此与图像处理相结合的成像技术已成为研究该组织的微观结构和生物力学的强大工具。在这里,我们提出了一种染色方法,以增强显微计算机断层扫描(micro-CT)成像中微观结构的对比度,以及使用microCT和二次谐波产生(SHG)显微镜成像的组织之间的比较。然后,我们应用Frangi的血管过滤器的修改版本来自动分割LC的结缔组织束,并确定每个束的方向。这种方法成功地将来自微型CT的猪视神经头部的光束分为三个维度,将SHG显微镜分为两个维度。作为此过滤器的一种应用,我们提出了后眼的有限元建模,表明结缔组织体积分数是LC生物力学的主要驱动因素。我们得出的结论是,使用Frangi滤波器进行分割是用于LC生物力学未来图像驱动研究的强大工具。

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