Abstract: A method is disclosed for segmentation of three dimensional image data sets, to obtain digital models of objects identifiable in the image data set. The image data set may be obtained from any convenient source, including medical imaging modalities, geological imaging, industrial imaging, and the like. A graph cuts method is applied to the image data set, and a level set method is then applied to the data using the output from the graph cuts method. The graph cuts process comprises determining location information for the digital data on a 3D graph, and cutting the 3D graph to determine approximate membership information for the object. The boundaries of the object is then refined using the level set method. Finally, a representation of the object volumes can be derived from an output of the level set method. Such representation may be used to generate rapid prototyped physical models of the objects.

Abstract: A hierarchy of deformation operations is implemented to deform a template and match the deformed template to an object in a video frame. At each level, the constraints on the template deformations are relaxed, while the spatial range of the object boundary search is narrowed. At a highest level, an initial template is translated, rotated and scaled to coarsely locate the object within a given image frame. At a middle level, an affine transformation is implemented, globally or locally, to deform the template. For a local affine transformation process, a sup-portion, such as an articulation or appendage portion of the template is deformed. The middle level refines the template to get the template boundary close to the actual object boundary within a given frame. At the lowest level, a local segmentation algorithm is applied to deform the now close boundary to finely match the object boundary.