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ISBI
2008
IEEE

Medial-based Bayesian tracking for vascular segmentation: Application to coronary arteries in 3D CT angiography

12 years 18 days ago
Medial-based Bayesian tracking for vascular segmentation: Application to coronary arteries in 3D CT angiography
We propose a new Bayesian, stochastic tracking algorithm for the segmentation of blood vessels from 3D medical image data. Inspired by the recent developments in particle filtering, it relies on a constrained, medial-based geometric model and on an original sampling scheme for the selection of tracking hypotheses. A key property of this new sampling scheme is the ability to take into account a distribution of hypotheses broader than similar methods such as classical particle filters, while remaining computationally efficient. The proposed method was applied to the challenging and medically critical task of coronary artery segmentation from 3D cardiac computed tomography (CT) images. Prior knowledge, injected in the process, was learned from a manually segmented database of 19 cases. Qualitative and quantitative evaluation is presented on clinical data, including pathologies and local anomalies.
David Lesage, Elsa D. Angelini, Isabelle Bloch, Ga
Added 20 Nov 2009
Updated 20 Nov 2009
Type Conference
Year 2008
Where ISBI
Authors David Lesage, Elsa D. Angelini, Isabelle Bloch, Gareth Funka-Lea
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