Deformable modeling for characterizing biomedical shape changes

Ferrant, M. Macq, Benoît [UCL] Nabavi, A Warfield, SK

We present a new algorithm for modeling and characterizing shape changes in 3D image sequences of biomedical structures. Our algorithm tracks the shape changes of the objects depicted in the image sequence using an active surface algorithm. To characterize the deformations of the surrounding and inner volume of the object's surfaces, we use a physics-based model of the objects the image represents. In the applications we are presenting, our physics-based model is linear elasticity and we solve the corresponding equilibrium equations using the Finite Element (FE) method. To generate a FE mesh from the initial 3D image, we have developed a new multiresolution tetrahedral mesh generation algorithm specifically suited for labeled image volumes. The shape changes of the surfaces of the objects are used as boundary conditions to our physics-based FE model and allow us to infer a volumetric deformation field from the surface deformations. Physics-based measures such as stress tensor maps can then be derived from our model for characterizing the shape changes of the objects in the image sequence. Experiments on synthetic images as well as on medical data show the performances of the algorithm.