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