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Type: Journal article
Title: Cardiac flow component analysis
Author: Wong, K.
Tu, J.
Kelso, R.
Worthley, S.
Sanders, P.
Mazumdar, J.
Abbott, D.
Citation: Medical Engineering & Physics, 2010; 32(2):174-188
Publisher: Elsevier Sci Ltd
Issue Date: 2010
ISSN: 1350-4533
Statement of
Kelvin K.L. Wong, Jiyuan Tu, Richard M. Kelso, Stephen G. Worthley, Prashanthan Sanders, Jagannath Mazumdar and Derek Abbott
Abstract: In a chamber of the heart, large-scale vortices are shown to exist as the result of the dynamic blood flow and unique morphological changes of the chamber wall. As the cardiovascular flow varies over a cardiac cycle, there is a need for a robust quantification method to analyze its vorticity and circulation. We attempt to measure vortex characteristics by means of two-dimensional vorticity maps and vortex circulation. First, we develop vortex component analysis by segmenting the vortices using an data clustering algorithm before histograms of their vorticity distribution are generated. The next stage is to generate the statistics of the vorticity maps for each phase of the cardiac cycle to allow analysis of the flow. This is followed by evaluating the circulation of each segmented vortex. The proposed approach is dedicated to examining vortices within the human heart chamber. The vorticity field can indicate the strength and number of large-scale vortices in the chamber. We provide the results of the flow analysis after vorticity map segmentation and the statistical properties that characterize the vorticity components. The success of the cardiac measurement and analysis is illustrated by a case study of the right atrium. Our investigation shows that it is possible to utilize a data clustering algorithm to segment vortices after vorticity mapping, and that the vorticity and circulation analysis of a chamber vorticity can provide new insights into the blood flow within the cardiovascular structure.
Keywords: Component flow analysis; Vorticity; Circulation; Phase contrast magnetic resonance imaging; Segmentation; Data clustering
Description: Copyright © 2009 IPEM Published by Elsevier Ltd.
RMID: 0020100006
DOI: 10.1016/j.medengphy.2009.11.007
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Appears in Collections:Electrical and Electronic Engineering publications

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