This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
Graph cut image segmentation with intensity information alone is prone to fail for objects with weak edges, in clutter, or under occlusion. Existing methods to incorporate shape a...
We present a method for segmenting the parts of multiple instances of a known object category exhibiting large variations in projected shape and colour. The method builds on an ex...
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...
Challenging object detection and segmentation tasks can be facilitated by the availability of a reference object. However, accounting for possible transformations between the diff...