KEYWORDS: Arteries, Detection and tracking algorithms, Image segmentation, Optical tracking, 3D image processing, Medical imaging, Data modeling, Image quality, Cancer, Medical research
Vessel tree tracking is an important and challenging task for many medical applications. This paper presents
a novel bifurcation detection algorithm for Bayesian tracking of vessel trees. Based on a cylindrical model, we
introduce a bifurcation metric that yields minimal values at potential branching points. This approach avoids
searching for bifurcations in every iteration of the tracking process (as proposed by prior works) and is therefore
computationally more efficient. We use the same geometric model for the bifurcation metric as for the tracking;
no specific bifurcation model is needed. In a preliminary evaluation of our method on 8 CTA datasets of coronary
arteries, all side branches and 95.8% of the main branches were detected correctly.
The random walker algorithm is a graph-based segmentation method that has become popular over the past few
years. The basis of the algorithm is a large, sparsely occupied system of linear equations, whose size corresponds
to the number of voxels in the image. To solve these systems, typically comprised of millions of equations,
the computational performance of conventional numerical solution methods (e.g. Gauss-Seidel) is no longer
satisfactory. An alternative method that has been described previously for solving 2D random walker problems
is the geometrical multigrid method. In this paper, we present a geometrical multigrid approach for the 3D
random walker problem. Our approach features an optimized calculation of the required Galerkin product and
a robust smoothing using the ILUβ method. To reach better convergence rates, the multigrid solver is used as a
preconditioner for the conjugate gradient solver. We compared the performance of our new multigrid approach
with the conjugate gradient solver on five MRI lung images with a resolution of 96 x 128 x 52 voxels. Initial
results show an increasing in speed of up to four times, reducing the average computation time from six minutes
to less than two minutes when using our proposed approach. Employing a multigrid solver for the random walker
algorithm thus permits accurate interactive segmentation with fewer delays.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.