4th IEEE Southwest Symposium on Image Analysis and Interpretation Tubular Objects Network Detection from 3D Images Austin, Texas April 02-April 04 ISBN: 0-7695-0595-3
We present an approach to the tree representation of a tubular objects network. The full-3D tracking algorithm for a single structure is detailed. Detection of bifurcations by a connectivity approach is then exposed. We show subvoxel accuracy and reliable orientation estimation for the tracking process on synthetic images. Bifurcations are also well detected on a complex synthetic image. Finally, applications of this method on real 3D medical images are shown. The method is particularly suited for processing Magnetic Resonance Angiography of the brain and neck.
Index Terms:
3D detection, tubular structures, network, vascular network, Magnetic Resonance Angiography
Citation:
N. Flasque, M. Desvignes, M. Revenu, J.M. Constans, "Tubular Objects Network Detection from 3D Images," ssiai, pp.96, 4th IEEE Southwest Symposium on Image Analysis and Interpretation, 2000 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||