Share Email Print
cover

Proceedings Paper

Graph-based bifurcation detection in phase-contrast MR images
Author(s): Yoo-Jin Jeong; Sebastian Ley; Michael Delles; Rüdiger Dillmann; Roland Unterhinninghofen
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Dealing with cardiovascular diseases the velocity-encoded magnetic resonance imaging (PC-MRI) is a well-known technique to acquire non-invasive measurements of the blood flow. However, the application of conventional vessel segmentation methods in PC-MR images often leads to problems due to the reduced quality of the morphology image. We proposed a robust centerline extraction method in PC-MR images to overcome those problems. The method yielded satisfying results for the centerline extraction of large vessels but did not consider vessel branches. Therefore, in this paper we present an approach for the detection of bifurcations in PC-MR images. The developed algorithm requires two inputs: the previously computed centerline points of the main vessel and a minimal user input. For each point on the centerline it determines, if there exists a bifurcation in the cross-sectional plane at that position. This is accomplished by an a* path finding algorithm, which computes the path costs for a potential bifurcation point to its corresponding center point. The path costs are determined by the combination of different features derived from the morphology and flow information. By comparison of all cost sums, bifurcations can be detected due to their low amount/value. The algorithm, evaluated on 7 volunteer and 12 patient PC-MRI datasets, yielded satisfying results.

Paper Details

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86691Z (13 March 2013); doi: 10.1117/12.2006880
Show Author Affiliations
Yoo-Jin Jeong, Karlsruhe Institute of Technology (Germany)
Sebastian Ley, Univ. Hospital Heidelberg (Germany)
Univ. of Toronto (Canada)
Michael Delles, Karlsruhe Institute of Technology (Germany)
Rüdiger Dillmann, Karlsruhe Institute of Technology (Germany)
Roland Unterhinninghofen, Karlsruhe Institute of Technology (Germany)


Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

© SPIE. Terms of Use
Back to Top