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通过连续图像膨胀量化膜间距离

Quantifying Intermembrane Distances with Serial Image Dilations.

作者信息

Raisch Tristan, Khan Momina, Poelzing Steven

机构信息

Virginia Tech Carilion Research Institute, Virginia Tech; Translational Biology, Medicine and Health, Virginia Tech.

Virginia Tech Carilion Research Institute, Virginia Tech.

出版信息

J Vis Exp. 2018 Sep 28(139):58311. doi: 10.3791/58311.

Abstract

A recently-described extracellular nanodomain, termed the perinexus, has been implicated in ephaptic coupling, which is an alternative mechanism for electrical conduction between cardiomyocytes. The current method for quantifying this space by manual segmentation is slow and has low spatial resolution.We developed an algorithm that uses serial image dilations of a binary outline to count the number of pixels between two opposing 2 dimensional edges.This algorithm requires fewer man hours and has a higher spatial resolution than the manual method while preserving the reproducibility of the manual process.In fact, experienced and novice investigators were able to recapitulate the results of a previous study with this new algorithm.The algorithm is limited by the human input needed to manually outline the perinexus and computational power mainly encumbered by a pre-existing pathfinding algorithm.However, the algorithm's high-throughput capabilities, high spatial resolution and reproducibility make it a versatile and robust measurement tool for use across a variety of applications requiring the measurement of the distance between any 2-dimensional (2D) edges.

摘要

最近描述的一种细胞外纳米结构域,称为周连接,与ephaptic偶联有关,ephaptic偶联是心肌细胞之间电传导的另一种机制。目前通过手动分割来量化这个空间的方法速度慢且空间分辨率低。我们开发了一种算法,该算法使用二进制轮廓的连续图像膨胀来计算两个相对的二维边缘之间的像素数量。与手动方法相比,该算法所需的人工时间更少,空间分辨率更高,同时保留了手动过程的可重复性。事实上,经验丰富和新手研究人员都能够使用这种新算法重现先前研究的结果。该算法受到手动勾勒周连接所需的人工输入以及主要由预先存在的路径查找算法所阻碍的计算能力的限制。然而,该算法的高通量能力、高空间分辨率和可重复性使其成为一种通用且强大的测量工具,可用于各种需要测量任意二维(2D)边缘之间距离的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3c8/6235350/794f1756d2df/jove-139-58311-0.jpg

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