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Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. 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.