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3D boundary extraction of the left ventricle by a deformable model with a priori information

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.