We propose a fully automated variation of the GrabCut technique for segmenting comparatively simple images with little variation in background colour and relatively high contrast ...
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 present two approaches for automatically segmenting the spinal cord/canal from native CT images of the thorax region containing the spine. Different strategies are included to ...
In this work we proposea new statistic deformable model that we call discriminant snake for 3D reconstruction in volumetric images. Our discriminant snake generalises the classica...
We present a novel variational approach to top-down image segmentation, which accounts for significant projective transformations between a single prior image and the image to be s...