Combined model-based segmentation and elastic registration for accurate quantification of the aortic arch

Authors:
Andreas Biesdorf;Karl Rohr;Hendrik von Tengg-Kobligk;Stefan Wörz
Affiliations:
University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg, Dept. Bioinformatics and Functional Genomics;University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg, Dept. Bioinformatics and Functional Genomics;German Cancer Research Center Heidelberg, Dept. of Radiology and University Hospital Heidelberg, Dept. of Diagnostic and Interventional Radiology;University of Heidelberg, BIOQUANT, IPMB, and DKFZ Heidelberg, Dept. Bioinformatics and Functional Genomics
Venue:
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part I
Year:
2010

Citing 2
Cited 0

Registration and Analysis of Vascular Images

International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Segmentation and Quantification of Human Vessels Using a 3-D Cylindrical Intensity Model

IEEE Transactions on Image Processing

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Abstract

Accurate quantification of the morphology of vessels is important for diagnosis and treatment of cardiovascular diseases. We introduce a new approach for the quantification of the aortic arch morphology that combines 3D model-based segmentation with elastic image registration. The performance of the approach has been evaluated using 3D synthetic images and clinically relevant 3D CTA images including pathologies. We also performed a comparison with a previous approach.