Share Email Print

Proceedings Paper

Vascular landmark detection in 3D CT data
Author(s): David Liu; S. Kevin Zhou; Dominik Bernhardt; Dorin Comaniciu
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

This work presents novel methods to accurately placing landmarks inside the vessel lumen. This task is an important prerequisite to automatic centerline tracing. Methods have been proposed in the past to determine the location of organ landmarks, and yet several challenges remain for vascular landmarks. First, placing landmarks inside the lumen could be challenging for narrow vessels. Second, contrast-enhanced arteries could be tightly surrounded by bones with similar intensity profiles, making detection difficult compared to arteries surrounded only by darker tissues. Third, landmarks not located at bifurcations could be ill-defined as they have high uncertainty in position. We first present a method to detect landmarks that are located at vessel bifurcations. Such landmarks have well-defined positions, and we detect them using machine learning techniques. We then present a method to detect vascular landmarks not located at bifurcations. First, a segment detector is created to detect a vessel segment. Annotating multiple points along a vessel segment is easier than annotating a single landmark position, as there is no well-defined position along a vessel. This resolves the ambiguity issue mentioned above. Second, spatial features are computed from the segment detector's response map, and a regression model is created which takes as input the local spatial features surrounding a voxel, and outputs a confidence score of how likely this voxel is inside the lumen. We evaluate the system on a set of 94 3D CT datasets.

Paper Details

Date Published: 15 March 2011
PDF: 7 pages
Proc. SPIE 7965, Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging, 796522 (15 March 2011); doi: 10.1117/12.878388
Show Author Affiliations
David Liu, Siemens Corporate Research (United States)
S. Kevin Zhou, Siemens Corporate Research (United States)
Dominik Bernhardt, Siemens Healthcare (Germany)
Dorin Comaniciu, Siemens Corporate Research (United States)

Published in SPIE Proceedings Vol. 7965:
Medical Imaging 2011: Biomedical Applications in Molecular, Structural, and Functional Imaging
John B. Weaver; Robert C. Molthen, Editor(s)

© SPIE. Terms of Use
Back to Top