Title :
Tubular objects network detection from 3D images
Author :
Flasque, N. ; Desvignes, M. ; Constans, J.M. ; Revenu, M.
Author_Institution :
ISMRA, Caen, France
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;
Conference_Titel :
Image Analysis and Interpretation, 2000. Proceedings. 4th IEEE Southwest Symposium
Conference_Location :
Austin, TX
Print_ISBN :
0-7695-0595-3
DOI :
10.1109/IAI.2000.839579
