Accurate Detection of 3D Tubular Tree Structures

Nicolas Flasque 1 Michel Desvignes 1 Jean-Marc Constans 2 Marinette Revenu 1
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : Spatial resolution of Magnetic Resonance Angiography (MRA) makes it a powerful tool for diagnosis and surgical planning. However, image interpretation and visualization tools are missing, and three-dimensional measurements are not usually accessible [6]. Flexible visualization of the whole vascular tree and precise quantification of phenomenons like carotid stenosis are applications of an automated processing of MRA [5]. Building an accurate model of a tubular objects network such as bronchi or blood vessels can provide a substantial help for 3D visualization and quantification [4]. We present the tracking algorithm of centrelines that makes very few assumptions on the structure grey-level profile. The main originality of this work is the accurate 3D centreline tracking process which provides subvoxel accuracy and deals with bifurcations. This approach has been successfully applied to the cerebral vasculature in MRA images.
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Communication dans un congrès
ICIP Int. Conf. on Image Processing, 2000, Vancouver, Canada. 3, pp.436-439, 2000
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Nicolas Flasque, Michel Desvignes, Jean-Marc Constans, Marinette Revenu. Accurate Detection of 3D Tubular Tree Structures. ICIP Int. Conf. on Image Processing, 2000, Vancouver, Canada. 3, pp.436-439, 2000. 〈hal-00960268〉

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