We propose a new approach to the problem of generating a simple topologically-c losed geometric model from a point-sampled volume data set. We call such a model a Geometrically Deformed Model or GDM. A GDM is created by placing a 'seed' model in the volume data set. The model is then deformed by a relaxation process that minimizes a set of constraints that provides a measure of bow well (be model tits the features in the data. Constraints are associated with each vertex in the model that

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... local deformation, interaction between the model and tbe data set. and the shape and topology of tbe model. Once generated, a GDM can be used for visualization. shape recognition, geometric measurements. or subjected to a series of geometric operations. This technique is of special importance because of the advent of nondestructive sensing equipment (CT, MRI ) that generates point samples of true three-dimensional objects.