NEFI: Network Extraction From Images

Abstract

Networks are amongst the central building blocks of many systems. Given a graph of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to study various types of networks. In some applications, graph acquisition is relatively simple. However, for many networks data collection relies on images where graph extraction requires domain-specific solutions. Here we introduce NEFI, a tool that extracts graphs from images of networks originating in various domains. Regarding previous work on graph extraction, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners to easily extract graphs from images by combining basic tools from image processing, computer vision and graph theory. Thus, NEFI constitutes an alternative to tedious manual graph extraction and special purpose tools. We anticipate NEFI to enable time-efficient collection of large datasets. The analysis of these novel datasets may open up the possibility to gain new insights into the structure and function of various networks. NEFI is open source and available at http://nefi.mpi-inf.mpg.de.

phenoVein - A tool for leaf vein segmentation and analysis

“…In the software LeafGUI, vein width calculation is based on the determination of the vein area and depends on user-defined thresholds (Price et al, 2011(Price et al, , 2012. With the software tool NEFI (Dirnberger et al, 2015), the width of veins can be visualized by using a watershed algorithm, but no data or validation measurements of the algorithm were presented.…”

“…A general overview on plant image analysis tools is collected in an online database at http://www.plant-imageanalysis.org (Lobet et al, 2013). Programs allowing automated or semiautomated analysis of leaf venation parameters are, for example, a method to extract leaf venation patterns (Rolland-Lagan et al, 2009), the leaf extraction and analysis framework graphical user interface LeafGUI (Price et al, 2011), the leaf image analysis interface LIMANI (Dhondt et al, 2012), the user-interactive vessel generation analysis tool VESGEN (Vickerman et al, 2009;Parsons-Wingerter et al, 2014), and the software network extraction from images NEFI (Dirnberger et al, 2015). Nevertheless, for the analysis of large-scale leaf vein phenotyping experiments, there are certain needs that are only partly covered by each of the approaches and programs mentioned above.…”

Automated analysis of Physarum network structure and dynamics

“…Various groups have developed methods to characterize the biological networks formed by fungi and slime molds [3,5,12,25,39], and efficient implementations are available to download that work well for well-defined networks (see for example [12,32]). The simplest method to identify the veins automatically is intensity-based segmentation of a bright-field transmission image to give a binary image, with ones representing the vein structure and zeros for the background.…”

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

“…Moreover, in order to precisely determine the network's topological properties, a mathematical graph-based representation of the network is also introduced. Most recently, a novel and generic platform called Network Extraction From Images (NEFI) has been developed by [1]. The platform provides a wide range of image pre-processing and segmentation techniques for network reconstruction and graph-based representation.…”

“…Particularly, biological networks widely studied by the bioimage informatics community [1], [2]. However, information of the content and complexity of biological networks in images vary significantly between different network subcategories, such as, the very high density of links in 2D leaf vein networks [3].…”