We introduce a new graph-theoretic approach to image segmentation based on minimizing a novel class of `mean cut' cost functions. Minimizing these cost functions corresponds ...
A global parametric shape model (boundary) of the object is optimized according to evidence accumulated from local features and the prior probability of the model parameters learn...
Standard image based segmentation approaches perform poorly when there is little or no contrast along boundaries of different regions. In such cases, segmentation is largely perfor...
Kilian M. Pohl, John W. Fisher III, Ron Kikinis, W...
We introduce a variational approach to image segmentation based on sparse coverings of image domains by shape templates. The objective function combines a data term that achieves ...
Dirk Breitenreicher, Jan Lellmann, Christoph Schn&...
Segmentation of medical images is challenging due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Consequently, this task involves ...