Pozo, JM, Geers, AJ and Frangi, AF orcid.org/0000-0002-2675-528X (2017) Information theoretic measurement of blood flow complexity in vessels and aneurysms: Interlacing complexity index. In: Lecture Notes in Computer Science. International Conference on Medical Image Computing and Computer-Assisted Intervention: MICCAI 2017, 10-14 Sep 2017, Quebec, Canada. Springer Verlag , pp. 233-241. ISBN 9783319661841
Abstract
Haemodynamics is believed to be a crucial factor in the aneurysm formation, evolution and eventual rupture. The 3D blood flow is typically derived by computational fluid dynamics (CFD) from patient-specific models obtained from angiographic images. Typical quantitative haemodynamic indices are local. Some qualitative classifications of global haemodynamic features have been proposed. However these classifications are subjective, depending on the operator visual inspection. In this work we introduce an information theoretic measurement of the blood flow complexity, based on Shannon’s Mutual Information, named Interlacing Complexity Index (ICI). ICI is an objective quantification of the flow complexity from aneurysm inlet to aneurysm outlets. It measures how unpredictable is the location of the streamlines at the outlets from knowing the location at the inlet, relative to the scale of observation. We selected from the @neurIST database a set of 49 cerebral vasculatures with aneurysms in the middle cerebral artery. Surface models of patient-specific vascular geometries were obtained by geodesic active region segmentation and manual correction, and unsteady flow simulations were performed imposing physiological flow boundary conditions. The obtained ICI has been compared to several qualitative classifications performed by an expert, revealing high correlations.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer International Publishing AG 2017. This is an author produced version of a conference paper published in Lecture Notes in Computer Science. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Aneurysms; CFD; Haemodynamics; Flow complexity; Mutual information |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 30 Apr 2019 12:59 |
Last Modified: | 30 Apr 2019 12:59 |
Status: | Published |
Publisher: | Springer Verlag |
Identification Number: | 10.1007/978-3-319-66185-8_27 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145302 |