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Lookup NU author(s): Professor Boguslaw ObaraORCiD
This is the authors' accepted manuscript of an article that has been published in its final definitive form by Institute of Physics Publishing, 2017.
For re-use rights please refer to the publisher's terms and conditions.
© 2017 IOP Publishing Ltd. We evaluate different ridge-enhancement and segmentation methods to automatically extract the network architecture from time-series of Physarum plasmodia withdrawing from an arena via a single exit. Whilst all methods gave reasonable results, judged by precision-recall analysis against a ground-truth skeleton, the mean phase angle (Feature Type) from intensity-independent, phase-congruency edge enhancement and watershed segmentation was the most robust to variation in threshold parameters. The resultant single pixel-wide segmented skeleton was converted to a graph representation as a set of weighted adjacency matrices containing the physical dimensions of each vein, and the inter-vein regions. We encapsulate the complete image processing and network analysis pipeline in a downloadable software package, and provide an extensive set of metrics that characterise the network structure, including hierarchical loop decomposition to analyse the nested structure of the developing network. In addition, the change in volume for each vein and intervening plasmodial sheet was used to predict the net flow across the network. The scaling relationships between predicted current, speed and shear force with vein radius were consistent with predictions from Murray's law. This work was presented at PhysNet 2015.
Author(s): Fricker MD, Akita D, Heaton LLM, Jones N, Obara B, Nakagaki T
Publication type: Article
Publication status: Published
Journal: Journal of Physics D: Applied Physics
Year: 2017
Volume: 50
Issue: 25
Online publication date: 06/06/2017
Acceptance date: 12/05/2017
Date deposited: 04/05/2021
ISSN (print): 0022-3727
ISSN (electronic): 1361-6463
Publisher: Institute of Physics Publishing
URL: https://doi.org/10.1088/1361-6463/aa72b9
DOI: 10.1088/1361-6463/aa72b9
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