DocumentCode :
725080
Title :
3D statistical models of the aorta and the supra-aortic branches
Author :
Worz, Stefan ; von Tengg-Kobligk, Hendrik ; Rohr, Karl
Author_Institution :
Dept. Bioinf. & Functional Genomics, Univ. of Heidelberg, Heidelberg, Germany
fYear :
2015
fDate :
16-19 April 2015
Firstpage :
1572
Lastpage :
1575
Abstract :
We introduce a new approach for creating 3D statistical models of the aorta and supra-aortic branches to investigate the variability of the human aorta based on MRA image data. The approach includes 3D segmentation and quantification using a novel curved cylindrical intensity model as well as 3D normalization and correspondence finding. In addition to a statistical model for all subjects we have also created individual models which are gender and age matched to determine age-related morphologic changes.
Keywords :
biomedical MRI; blood vessels; cardiovascular system; image segmentation; medical image processing; statistical analysis; 3D normalization; 3D segmentation; 3D statistical models; MRA image data; age-related morphologic changes; aorta; correspondence finding; curved cylindrical intensity model; magnetic resonance angiography; supra-aortic branches; Biomedical imaging; Image segmentation; Morphology; Shape; Solid modeling; Standards; Three-dimensional displays; 3D MRA; 3D curved cylindrical intensity model; 4D PDM; Statistical aorta model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
Conference_Location :
New York, NY
Type :
conf
DOI :
10.1109/ISBI.2015.7164179
Filename :
7164179
Link To Document :
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