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Dipl.-Ing. Maria Polyanskaya

Alumnus of the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

Quantitative 3D imaging of the coronary vessels in C-arm CT data

Left coronary artery: originally reconstructed volume
3D vessel segmentation
3D vessel centerline extraction
Lumen segmentation in 2D projection image
3D vessel tree model

3D imaging of the coronary tree from a single 5s rotational angiography is challenging due to the cardiac motion. Recent techniques [1] achieve 3D reconstruction of the coronary tree by estimating and compensating the coronary motion field. However, that method is not quantitative and does not allow precise measurement of the size of vessels. This work aims at providing quantitative 3D measurements of the vessel geometry.


Our goal is to achieve geometric properties by using the non-quantitative 3D image segmentation results as a starting point. The accurate lumen size can be estimated from 2D projection images which capture the instant image and therefore do not suffer of the motion artefacts. Merging 3D-topology and 2D-size information results in the desired representation of 3D coronary vessel tree allowing to perform measurements of geometrical parameters.





 [1] Rohkohl, Christopher; Lauritsch, Günter; Prümmer, Marcus; Hornegger, Joachim Interventional 4-D Motion Estimation and Reconstruction of Cardiac Vasculature without Motion Periodicity Assumption In: Medical Image Computing and Computer-Assisted Intervention -  MICCAI 2009 London, UK 20-24 September 2009, Vol. Lecture Notes in Computer Science, 5761


 [*] Image data courtesy of Prof. Dr. J. Brachmann and Dr. H. Rittger, Klinikum Coburg, Germany