Adaptive constrained constructive optimisation for complex vascularisation processes.

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dc.contributor.author Talou, Gonzalo Daniel Maso
dc.contributor.author Safaei, Soroush
dc.contributor.author Hunter, Peter John
dc.contributor.author Blanco, Pablo Javier
dc.coverage.spatial England
dc.date.accessioned 2022-06-21T02:46:02Z
dc.date.available 2022-06-21T02:46:02Z
dc.date.issued 2021-03-17
dc.identifier.citation (2021). Scientific Reports, 11(1), 6180-.
dc.identifier.issn 2045-2322
dc.identifier.uri https://hdl.handle.net/2292/60054
dc.description.abstract Mimicking angiogenetic processes in vascular territories acquires importance in the analysis of the multi-scale circulatory cascade and the coupling between blood flow and cell function. The present work extends, in several aspects, the Constrained Constructive Optimisation (CCO) algorithm to tackle complex automatic vascularisation tasks. The main extensions are based on the integration of adaptive optimisation criteria and multi-staged space-filling strategies which enhance the modelling capabilities of CCO for specific vascular architectures. Moreover, this vascular outgrowth can be performed either from scratch or from an existing network of vessels. Hence, the vascular territory is defined as a partition of vascular, avascular and carriage domains (the last one contains vessels but not terminals) allowing one to model complex vascular domains. In turn, the multi-staged space-filling approach allows one to delineate a sequence of biologically-inspired stages during the vascularisation process by exploiting different constraints, optimisation strategies and domain partitions stage by stage, improving the consistency with the architectural hierarchy observed in anatomical structures. With these features, the aDaptive CCO (DCCO) algorithm proposed here aims at improving the modelled network anatomy. The capabilities of the DCCO algorithm are assessed with a number of anatomically realistic scenarios.
dc.format.medium Electronic
dc.language eng
dc.publisher Springer Science and Business Media LLC
dc.relation.ispartofseries Scientific reports
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher.
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject Arteries
dc.subject Humans
dc.subject Algorithms
dc.subject Models, Cardiovascular
dc.subject Models, Anatomic
dc.subject Computer Simulation
dc.subject Hemodynamics
dc.subject 1.1 Normal biological development and functioning
dc.subject Science & Technology
dc.subject Multidisciplinary Sciences
dc.subject Science & Technology - Other Topics
dc.title Adaptive constrained constructive optimisation for complex vascularisation processes.
dc.type Journal Article
dc.identifier.doi 10.1038/s41598-021-85434-9
pubs.issue 1
pubs.begin-page 6180
pubs.volume 11
dc.date.updated 2022-05-17T00:11:32Z
dc.rights.holder Copyright: The author en
dc.identifier.pmid 33731776 (pubmed)
pubs.author-url https://www.ncbi.nlm.nih.gov/pubmed/33731776
pubs.publication-status Published
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.subtype Research Support, Non-U.S. Gov't
pubs.subtype research-article
pubs.subtype Journal Article
pubs.elements-id 778806
pubs.org-id Bioengineering Institute
pubs.org-id Science
pubs.org-id Science Research
pubs.org-id ABI Associates
pubs.org-id Maurice Wilkins Centre (2010-2014)
dc.identifier.eissn 2045-2322
dc.identifier.pii 10.1038/s41598-021-85434-9
pubs.number 6180
pubs.record-created-at-source-date 2022-05-17
pubs.online-publication-date 2021-03-17


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