We introduce a new method for segmentation of 3D medical data based on geometric variational principles. A minimal variance criterion is coupled with a geometric edge alignment mea...
Michal Holtzman-Gazit, Dorith Goldsher, Ron Kimmel
We develop a computational model of shape that extends existing Riemannian models of shape of curves to multidimensional objects of general topological type. We construct shape sp...
Xiuwen Liu, Yonggang Shi, Ivo D. Dinov, Washington...
A probabilistic deformable model for the representation of brain structures is described. The statistically learned deformable model represents the relative location of head (skull...
Deformable contours are now widely used in image segmentation, using different models, criteria and numeric schemes. Some theoretical comparisons between few deformable model met...
Abstract. This paper describes the construction of 3D dynamic statistical deformable models for complex topological shapes. It significantly extents the existing framework in that ...