2D Adaptive Grid-Based Image Analysis Approach for Biological Networks

Haifa F. Alhasson, B. Obara
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Abstract

The accurate analysis of biological networks, enabled by the precise capture of their individual components, can reveal important underlying biological principles. Efficient image processing techniques are required to precisely identify and quantify the networks from complex images. In this paper, we present a novel approach for a weighted and undirected graph-based network reconstruction and quantification from 2D images using an adaptive rectangular mesh refinement approach. The proposed approach is able to efficiently identify the organizational principles of the network, capturing the underlying network structure, and computing relevant network topological properties. We validate the proposed approach by comparing it with the state-of-the-art method.
生物网络二维自适应网格图像分析方法
对生物网络的精确分析,通过对其单个组成部分的精确捕捉,可以揭示重要的潜在生物学原理。需要有效的图像处理技术来精确地识别和量化复杂图像中的网络。在本文中,我们提出了一种利用自适应矩形网格细化方法对二维图像进行加权无向图网络重建和量化的新方法。该方法能够有效地识别网络的组织原则,捕获底层网络结构,并计算相关的网络拓扑属性。我们通过将其与最先进的方法进行比较来验证所提出的方法。
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