Vortex Detection in 4D MRI Data: Using the Proper Orthogonal Decomposition for Improved Noise-Robustness
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Recent advances in magnetic resonance imaging (MRI) technology enabled the acquisition of time-resolved 3Dblood flow data. Several flow visualization methods have been applied to these data in order to investigate linksbetween cardiovascular diseases and hemodynamic phenomena, such as vortices in the blood flow. In this work,we investigate the use of the proper orthogonal decomposition (POD) for the preprocessing of MRI datasets andstudy its effects with the l2 vortex detection method. By comparing the POD method with the commonly usedGaussian filtering, we show that for comparable filtering strengths, the POD produces qualitatively better results.
Description
@inproceedings{10.2312:eurovisshort.20141169,
booktitle = {EuroVis - Short Papers},
editor = {N. Elmqvist and M. Hlawitschka and J. Kennedy},
title = {{Vortex Detection in 4D MRI Data: Using the Proper Orthogonal Decomposition for Improved Noise-Robustness}},
author = {Carnecky, Robert and Brunner, Thomas and Born, Silvia and Waser, Jürgen and Heine, Christian and Peikert, Ronald},
year = {2014},
publisher = {The Eurographics Association},
ISBN = {978-3-905674-69-9},
DOI = {10.2312/eurovisshort.20141169}
}