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From a set of longitudinal three-dimensional scans of the same anatomical structure, we have accurately modeled the temporal shape and size changes using a linear shape model. On a total of 31 computed tomography scans of the mandible from six patients, 14,851 semilandmarks are found automatically using shape features and a new algorithm called… (More)

Assume that only partial knowledge about a non-rigid registration is given: certain points, curves or surfaces in one 3D image are known to map to certain points, curves or surfaces in another 3D image. In trying to identify the non-rigid displacement field, we face a generalized aperture problem since along the curves and surfaces, point correspondences… (More)

Given a sparse set of feature matches, we want to compute an interpolated dense displacement map. The application may be stereo d i s p arity computation, ow computation, or non-rigid medical registration. Also estimation of missing image data, may be phrased in this framework. Since the features often are very sparse, the interpolation model becomes… (More)

From a set of temporally separated scannings of the same anatomical structure we w i s h t o i d e n tify and analyze the growth in terms of a metamorphosis. That is, we study the temporal change of shape which m a y provide an understanding of the biological processes which govern the growth process. We subdivide the growth analysis into growth simulation,… (More)

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