@InProceedings{freedman:cvprw04,
  author =	 {D.\ Freedman and R.\ J.\ Radke and Tao Zhang and
                  Yongwon Jeong and G.\ T.\ Y.\ Chen},
  title =	 {Model-Based Multi-Object Segmentation via
                  Distribution Matching},
  booktitle =	 {Computer Vision and Pattern Recognition Workshop,
                  2004 Conference on},
  year =	 2004,
  pages =	 {11--11},
  keywords =	 {deformable segmentation, medical image segmentation,
                  prostate segmentation, shape and appearance model},
  abstract =	 {A new algorithm for the segmentation of objects from
                  3D images using deformable models is presented. This
                  algorithm relies on learned shape and appearance
                  models for the objects of interest. The main
                  innovation over similar approaches is that there is
                  no need to compute a pixelwise correspondence
                  between the model and the image; instead,
                  probability distributions are compared. This allows
                  for a faster, more principled
                  algorithm. Furthermore, the algorithm is not
                  sensitive to the form of the shape model, making it
                  quite flexible. Results of the algorithm are shown
                  for the segmentation of the prostate and bladder
                  from medical images.},
  annote =	 {}
}