3D boundary extraction of the left ventricle by a deformable model with a priori information
- 19 November 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 492-495
- https://doi.org/10.1109/icip.1995.537523
Abstract
In medical imaging, 3D boundary extraction is a preliminary requisite for a coherent shape analysis of an organ. Deformable objects, like the heart cavities, are often hard to detect because of the artefacts caused by the motion. The authors present a 3D deformable surface model based on a parameterized representation combined with a random process of deformation. The solution is searched for by the minimization of an energy function through simulated annealing. The authors also discuss the introduction of a priori shape information about the object. The boundary extraction algorithm is applied to 3D CT data of a dog's heart.Keywords
This publication has 13 references indexed in Scilit:
- Surface shape and curvature scalesPublished by Elsevier ,2003
- 3D representation and deformation analysis of the heart walls from X-ray and MR imagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Parametrization of Closed Surfaces for 3-D Shape DescriptionComputer Vision and Image Understanding, 1995
- Active Shape Models-Their Training and ApplicationComputer Vision and Image Understanding, 1995
- A Fast algorithm for active contours and curvature estimationCVGIP: Image Understanding, 1992
- Dynamic 3D models with local and global deformations: deformable superquadricsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Structural Image Restoration through Deformable TemplatesJournal of the American Statistical Association, 1991
- Using dynamic programming for solving variational problems in visionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1990
- Automatic ventricular cavity boundary detection from sequential ultrasound images using simulated annealingIEEE Transactions on Medical Imaging, 1989
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of ImagesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1984