Tubular objects network detection from 3D images

Author

Flasque, N. ; Desvignes, M. ; Constans, J.M. ; Revenu, M.

Author_Institution

ISMRA, Caen, France

fYear

2000

fDate

2000

Firstpage

96

Lastpage

100

Abstract

We present an approach to the tree representation of a tubular object network. The full 3D tracking algorithm for a single tubular 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 to real 3D medical images are shown. The method is particularly suited for processing magnetic resonance angiography of the brain and neck

Keywords

bifurcation; biomedical MRI; brain; estimation theory; medical image processing; object detection; tracking; tree data structures; 3D medical images; 3D tracking algorithm; bifurcations; brain; complex synthetic image; connectivity approach; magnetic resonance angiography; medical image processing; neck; object detection; reliable orientation estimation; subvoxel accuracy; tree representation; tubular object network; Angiography; Bifurcation; Blood vessels; Electrical capacitance tomography; Magnetic resonance; Object detection; Respiratory system; Spatial resolution; Surgery; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Analysis and Interpretation, 2000. Proceedings. 4th IEEE Southwest Symposium

Conference_Location

Austin, TX

Print_ISBN

0-7695-0595-3

Type

conf

DOI

10.1109/IAI.2000.839579

Filename

839579